Method and apparatus for optimizing resource allocation in joint phase time arrays wireless communication system

Abstract

The present disclosure relates to a 5G communication system or a 6G communication system for supporting higher data rates beyond a 4G communication system such as long term evolution (LTE). Method and system for optimizing resource allocation in Joint Phase Time Arrays are disclosed. Method includes creating sorted Resource Block (RB) list based on frequency-selective beam gains of RBs. Sorted RB list comprises RBs in descending order based on frequency-selective beam gain. Method includes calculating Signal-to-Noise Ratio (SNR) for each RB in sorted RB list, based on wideband SNR corresponding to user equipment (UE) and frequency-selective beam gain. Method includes computing throughput value, for each of a combination of calculated SNRs and for associated Modulation and Coding Scheme (MCS) values. Method includes determining optimal MCS value and optimal number of RBs for UEs based on computed throughput value and wideband SNR.

Description

METHOD AND APPARATUS FOR OPTIMIZING RESOURCE ALLOCATION IN JOINT PHASE TIME ARRAYS WIRELESS COMMUNICATION SYSTEM

[0001] The present disclosure relates to the field of wireless communication, and more particularly, relates to a method and an apparatus for optimizing resource allocation in a Joint Phase Time Arrays (JPTA) wireless communication system.

[0002] Considering the development of wireless communication from generation to generation, the technologies have been developed mainly for services targeting humans, such as voice calls, multimedia services, and data services. Following the commercialization of 5G (5th-generation) communication systems, it is expected that the number of connected devices will exponentially grow. Increasingly, these will be connected to communication networks. Examples of connected things may include vehicles, robots, drones, home appliances, displays, smart sensors connected to various infrastructures, construction machines, and factory equipment. Mobile devices are expected to evolve in various form-factors, such as augmented reality glasses, virtual reality headsets, and hologram devices. In order to provide various services by connecting hundreds of billions of devices and things in the 6G (6th-generation) era, there have been ongoing efforts to develop improved 6G communication systems. For these reasons, 6G communication systems are referred to as beyond-5G systems.

[0003] 6G communication systems, which are expected to be commercialized around 2030, will have a peak data rate of tera (1,000 giga)-level bps and a radio latency less than 100μsec, and thus will be 50 times as fast as 5G communication systems and have the 1 / 10 radio latency thereof.

[0004] In order to accomplish such a high data rate and an ultra-low latency, it has been considered to implement 6G communication systems in a terahertz band (for example, 95GHz to 3THz bands). It is expected that, due to severer path loss and atmospheric absorption in the terahertz bands than those in mmWave bands introduced in 5G, technologies capable of securing the signal transmission distance (that is, coverage) will become more crucial. It is necessary to develop, as major technologies for securing the coverage, radio frequency (RF) elements, antennas, novel waveforms having a better coverage than orthogonal frequency division multiplexing (OFDM), beamforming and massive multiple input multiple output (MIMO), full dimensional MIMO (FD-MIMO), array antennas, and multiantenna transmission technologies such as large-scale antennas. In addition, there has been ongoing discussion on new technologies for improving the coverage of terahertz-band signals, such as metamaterial-based lenses and antennas, orbital angular momentum (OAM), and reconfigurable intelligent surface (RIS).

[0005] Moreover, in order to improve the spectral efficiency and the overall network performances, the following technologies have been developed for 6G communication systems: a full-duplex technology for enabling an uplink transmission and a downlink transmission to simultaneously use the same frequency resource at the same time; a network technology for utilizing satellites, high-altitude platform stations (HAPS), and the like in an integrated manner; an improved network structure for supporting mobile base stations and the like and enabling network operation optimization and automation and the like; a dynamic spectrum sharing technology via collison avoidance based on a prediction of spectrum usage; an use of artificial intelligence (AI) in wireless communication for improvement of overall network operation by utilizing AI from a designing phase for developing 6G and internalizing end-to-end AI support functions; and a next-generation distributed computing technology for overcoming the limit of UE computing ability through reachable super-high-performance communication and computing resources (such as mobile edge computing (MEC), clouds, and the like) over the network. In addition, through designing new protocols to be used in 6G communication systems, developing mecahnisms for implementing a hardware-based security environment and safe use of data, and developing technologies for maintaining privacy, attempts to strengthen the connectivity between devices, optimize the network, promote softwarization of network entities, and increase the openness of wireless communications are continuing.

[0006] It is expected that research and development of 6G communication systems in hyper-connectivity, including person to machine (P2M) as well as machine to machine (M2M), will allow the next hyper-connected experience. Particularly, it is expected that services such as truly immersive extended reality (XR), high-fidelity mobile hologram, and digital replica could be provided through 6G communication systems. In addition, services such as remote surgery for security and reliability enhancement, industrial automation, and emergency response will be provided through the 6G communication system such that the technologies could be applied in various fields such as industry, medical care, automobiles, and home appliances.

[0007] Embodiments of the present disclosure is to provide an apparatus and method for effectively providing a service in a wireless communication system.

[0008] In an embodiment, a method performed by a base station in a wireless communication system is provided. The method includes creating a sorted Resource Block (RB) list based on frequency-selective beam gains of a plurality of RBs, wherein the sorted RB list comprises the plurality of RBs in a descending order based on the corresponding frequency-selective beam gain; calculating a Signal-to-Noise Ratio (SNR) for each RB in the sorted RB list, based on a wideband SNR corresponding to a user equipment (UE) among a plurality of UEs and frequency-selective beam gain corresponding to the RB; computing a throughput value, for each of a combination of one or more calculated SNRs corresponding to the plurality of RBs and for associated Modulation and Coding Scheme (MCS) values corresponding to the plurality of RBs; determining an optimal MCS value and an optimal number of RBs for each of the plurality of UEs based on the computed throughput value and the wideband SNR for the corresponding UE; generating a mapping of the wideband SNR to the optimal number of RBs and the corresponding optimal MCS value; and allocating at least one of a number of RBs, corresponding RB indices, and corresponding MCS value to one or more UEs among the plurality of UEs using the mapping.

[0009] In an embodiment, a base station in a wireless communication system is provided. The base station includes at least one transceiver; at least one processor communicatively coupled to the at least one transceiver; and at least one memory, communicatively coupled to the at least one processor, storing instructions executable by the at least one processor individually or in any combination to cause the base station to create a sorted Resource Block (RB) list based on frequency-selective beam gains of a plurality of RBs, wherein the sorted RB list comprises the plurality of RBs in a descending order based on the corresponding frequency-selective beam gain, calculate a Signal-to-Noise Ratio (SNR) for each RB in the sorted RB list, based on a wideband SNR corresponding to a user equipment (UE) among a plurality of UEs and frequency-selective beam gain corresponding to the RB, compute a throughput value, for each of a combination of one or more calculated SNRs corresponding to the plurality of RBs and for associated Modulation and Coding Scheme (MCS) values corresponding to the plurality of RBs, determine an optimal MCS value and an optimal number of RBs for each of the plurality of UEs based on the computed throughput value and the wideband SNR for the corresponding UE, generate a mapping of the wideband SNR to the optimal number of RBs and the corresponding optimal MCS value, and allocate at least one of a number of RBs, corresponding RB indices, and corresponding MCS value to one or more UEs among the plurality of UEs using the mapping.

[0010] This summary is provided to introduce a selection of concepts, in a simplified format, that are further described in the detailed description of the invention. This summary is neither intended to identify essential inventive concepts of the invention nor is it intended to determine the scope of the invention.

[0011] According to an embodiment, a method for optimizing resource allocation in a Joint Phase Time Arrays (JPTA) wireless communication system is disclosed. The method includes creating a sorted Resource Block (RB) list based on frequency-selective beam gains of a plurality of RBs. The sorted RB list comprises the plurality of RBs in a descending order based on the corresponding frequency-selective beam gain. The method further includes calculating a Signal-to-Noise Ratio (SNR) for each RB in the sorted RB list, based on a wideband SNR corresponding to a user equipment (UE) among a plurality of UEs and frequency-selective beam gain corresponding to the RB. Furthermore, the method includes computing a throughput value for each of a combination of one or more calculated SNRs corresponding to the plurality of RBs and for associated Modulation and Coding Scheme (MCS) values corresponding to the plurality of RBs. The method includes determining an optimal MCS value and an optimal number of RBs for each of the plurality of UEs based on the computed throughput value and the wideband SNR for the corresponding UE. The method further includes generating a mapping of the wideband SNR to the optimal number of RBs and the corresponding optimal MCS value. Additionally, the method includes allocating at least one of a number of RBs, corresponding RB indices, and corresponding MCS values to one or more UEs among the plurality of UEs using the mapping.

[0012] According to an embodiment, a system for optimizing resource allocation in a Joint Phase Time Arrays (JPTA) wireless communication system is disclosed. The system includes a memory and a processor coupled to the memory. The processor is configured to create a sorted Resource Block (RB) list based on frequency-selective beam gains of a plurality of RBs. The sorted RB list comprises the plurality of RBs in a descending order based on the corresponding frequency-selective beam gain. The processor is further configured to calculate a Signal-to-Noise Ratio (SNR) for each RB in the sorted RB list, based on a wideband SNR corresponding to a user equipment (UE) among a plurality of UEs and frequency-selective beam gain corresponding to the RB.

[0013] The processor is configured to compute a throughput value for each of a combination of one or more calculated SNRs corresponding to the plurality of RBs and for associated Modulation and Coding Scheme (MCS) values corresponding to the plurality of RBs. Furthermore, the processor is configured to determine an optimal MCS value and an optimal number of RBs for each of the plurality of UEs based on the computed throughput value and the wideband SNR for the corresponding UE. Additionally, the processor is configured to generate a mapping of the wideband SNR to the optimal number of RBs and the corresponding optimal MCS value. The processor is further configured to allocate at least one of a number of RBs, corresponding RB indices, and corresponding MCS values to one or more UEs among the plurality of UEs using the mapping.

[0014] To further clarify the advantages and features of the present invention, a more particular description of the invention will be rendered by reference to specific embodiments thereof, which are illustrated in the appended drawings. It is appreciated that these drawings depict only typical embodiments of the invention and are therefore not to be considered limiting of its scope. The invention will be described and explained with additional specificity and detail in the accompanying drawings.

[0015] Embodiments of the present disclosure provides an apparatus and method for effectively providing a service in a wireless communication system.

[0016] These and other features, aspects, and advantages of the present invention will become better understood when the following detailed description is read with reference to the accompanying drawings in which like characters represent like parts throughout the drawings, wherein:

[0017] Figures 1Aillustrates a hybrid beamforming architecture;

[0018] Figures 1Billustrates a hybrid beamforming architecture;

[0019] Figure 1Cillustrates a Join Phase Time Arrays (JPTA) architecture;

[0020] Figures 1Dillustrates a conventional hybrid beamforming;

[0021] Figures 1Eillustrates a conventional hybrid beamforming;

[0022] Figures 1Fillustrates the JPTA;

[0023] Figures 1Gillustrates the JPTA;

[0024] Figures 1Hillustrates two beam case simulations;

[0025] Figures 1Iillustrates two beam case simulations;

[0026] Figures 1Jillustrates two beam case simulations;

[0027] Figures 1Killustrates four beam case simulations;

[0028] Figures 1Lillustrates four beam case simulations;

[0029] Figures 1Millustrates four beam case simulations;

[0030] Figures 1Nillustrates a link-level simulation of the four-beam case and the two-beam case, respectively;

[0031] Figures 1Oillustrates a link-level simulation of the four-beam case and the two-beam case, respectively;

[0032] Figure 1Pillustrates a graphical representation of beam gain and frequency;

[0033] Figure 2illustrates an exemplary environment of a Joint Phase Time Arrays (JPTA) wireless communication system for the implementation of a system to optimize resource allocation, according to an embodiment of the present disclosure;

[0034] Figure 3illustrates a process flow of the system for determining a number of JPTA beams to be used,according to an embodiment of the present disclosure;

[0035] Figure 4illustrates a process flow of the system for determining the number of JPTA beams to be used, according to an embodiment of the present disclosure;

[0036] Figure 5illustrates a process flow of the system for scheduling the UEs on ith JPTA beam, according to an embodiment of the present disclosure;

[0037] Figure 6illustrates a process flow of the system for determining resource block (RB) indices and MCS for each scheduled UE, according to an embodiment of the present disclosure;

[0038] Figure 7aillustrates a use case scenario illustrating a scheduling of one UE per beam in the JPTA wireless communication system, in accordance with the present disclosure;

[0039] Figure 7billustrates a graphical representation of a beam gain with frequency when one UE is scheduled per beam, in accordance with the present disclosure;

[0040] Figure 8aillustrates a use case scenario illustrating the scheduling of two UEs per beam in the JPTA wireless communication system, in accordance with the present disclosure;

[0041] Figure 8billustrates a graphical representation of a beam gain with frequency when two UEs are scheduled per beam, in accordance with the present disclosure;

[0042] Figure 9aillustrates a use case scenario illustrating the scheduling of more than two UEs per beam in the JPTA wireless communication system, in accordance with the present disclosure;

[0043] Figure 9billustrates a graphical representation of a beam gain with frequency when more than two UEs are scheduled per beam, in accordance with the present disclosure;

[0044] Figure 10illustrates an exemplary process flow for a method for predicting the DCD score, according to an embodiment of the present disclosure;

[0045] Figure 11illustrates a plot for SNR versus optimal RBs and MCS, according to an embodiment of the present disclosure;

[0046] Figures 12aillustrates a plot of SNR versus maximum achievable throughput for PAA and JPTA corresponding to four UEs with optimal RB allocation and full band allocation, according to an embodiment of the present disclosure;

[0047] Figures 12billustrates a plot of SNR versus maximum achievable throughput for PAA and JPTA corresponding to four UEs with optimal RB allocation and full band allocation, according to an embodiment of the present disclosure;

[0048] Figure 13illustrates a plot for percentage loss when all the 66 available RBs are used as a function of SNR, according to an embodiment of the present disclosure; and

[0049] Figure 14illustrates a plot showing the difference between the SNR and the EESM as a function of SNR, according to an embodiment of the present disclosure.

[0050] Further, skilled artisans will appreciate that elements in the drawings are illustrated for simplicity and may not have necessarily been drawn to scale. For example, the flow charts illustrate the method in terms of the most prominent steps involved to help improve understanding of aspects of the present invention. Furthermore, in terms of the construction of the device, one or more components of the device may have been represented in the drawings by conventional symbols, and the drawings may show only those specific details that are pertinent to understanding the embodiments of the present invention so as not to obscure the drawings with details that will be readily apparent to those of ordinary skill in the art having the benefit of the description herein.

[0051] For the purpose of promoting an understanding of the principles of the invention, reference will now be made to the various embodiments, and specific language will be used to describe the same. It will nevertheless be understood that no limitation of the scope of the invention is thereby intended, such alterations and further modifications in the illustrated system, and such further applications of the principles of the invention as illustrated therein being contemplated as would normally occur to one skilled in the art to which the invention relates.

[0052] It will be understood by those skilled in the art that the foregoing general description and the following detailed description are explanatory of the invention and are not intended to be restrictive thereof.

[0053] Reference throughout this specification to "an aspect", "another aspect" or similar language means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, appearances of the phrase "in an embodiment", "in another embodiment", and similar language throughout this specification may, but do not necessarily, all refer to the same embodiment.

[0054] The terms "comprise", "comprising" or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process or method that comprises a list of steps does not include only those steps but may include other steps not expressly listed or inherent to such process or method. Similarly, one or more devices or sub-systems or elements or structures or components preceded by "comprises... a" do not, without more constraints, preclude the existence of other devices or other sub-systems or other elements or other structures or other components or additional devices or additional sub-systems or additional elements or additional structures or additional components.

[0055] With recent developments in wireless communication, a growing demand for ultra-high data rates has placed immense pressure on the limited spectrum available in radio frequencies below 6 GHz (also referred to as sub-6 GHz). As a result, there is increasing interest in higher frequency bands, particularly Millimeter Wave (mmWave) and Terahertz (THz) bands, which offer significantly larger bandwidths. The mmWave band spans from 30 GHz to 300 GHz, corresponding to wavelengths between 10 mm and 1 mm, and is part of an Extremely High Frequency (EHF) spectrum. The mmWave and THz bands support multi-gigabit-per-second data rates, low latency, and high capacity, making them ideal for next-generation wireless networks. However, mmWave signals also face challenges such as high propagation loss, limited penetration through obstacles, and sensitivity to atmospheric conditions.

[0056] At the mmWave frequencies, mmWave signals experience severe attenuation due to high path loss, for example, due to the reason that the signal weakens significantly while traveling through the air. To overcome weakening of the signal, a beamforming technique is employed. The beamforming technique focuses the signal energy in a specific direction rather than spreading it out in all directions. The beam formation is achieved using large antenna arrays, which consist of many small antennas working together to direct the signal more precisely. As a result, the large antenna arrays are a common and effective solution for enhancing signal strength and coverage in mmWave systems.

[0057] Further, the integration of Multiple Input Multiple Output (MIMO) technology with the mmWave frequencies has revolutionized wireless communications, especially in the emerging landscape of 6G networks.

[0058] In MIMO systems operating in the sub-6 GHz frequency band, precoding is typically performed in a digital baseband domain using fully digital precoders. The digital precoders are capable of adjusting both the magnitude and phase of transmitted signals, allowing for precise beamforming and interference mitigation. However, fully digital precoding requires at least a separate Radio Frequency (RF) chain for each antenna element. The RF chain includes essential components such as mixers, filters, power amplifiers, and Analog-to-Digital Converters (ADCs), which collectively convert baseband signals into RF signals and vice versa. While such architecture is generally feasible at lower frequencies with fewer antennas, such an architecture becomes impractical at mmWave frequencies. The components of the RF chain become increasingly power-consuming and thermally demanding as operating frequencies rise into the mmWave range. Hence, the use of a large number of RF chains is prohibitive.

[0059] Further, in mmWave MIMO systems, the antenna elements are much smaller and more densely packed due to the shorter wavelengths. Such high density makes the mmWave systems extremely challenging to integrate the RF chains behind each antenna element, both in terms of physical space and power consumption. As a result, the mmWave MIMO systems often adopt hybrid precoding architectures. The hybrid precoding architectures combine a smaller number of RF chains with analog phase shifters to approximate the performance of fully digital systems while reducing hardware complexity and energy demands. The hybrid precoding architecture also splits the precoding process between the digital baseband domain and the analog RF domain. Further, in the hybrid precoding architecture, a reduced number of RF chains are used, and analog phase shifters or switches are employed to steer beams across multiple antenna elements. The hybrid precoding architecture significantly reduces hardware complexity and power consumption while still enabling effective beamforming and spatial multiplexing. The hybrid architecture thus strikes a balance between performance and efficiency, making it a practical solution for high-frequency, high-capacity wireless systems such as 5G and beyond. Therefore, the mmWave MIMO systems adopt the hybrid architecture to use fewer RF chains, where precoding is accomplished in both analog and digital domains.

[0060] As an alternative, hybrid beamforming is connected to each of the large number of antenna elements via low-cost analog phase shifters. In hybrid beam includes an analog beamforming, which uses analog phase shifters to steer beams at the RF level, and a digital beamforming, which manipulates signals in the baseband using digital precoding.

[0061] Figures 1Aand1Billustrate a hybrid beamforming architecture 100a, 110b. Referring to Figure 1A, the hybrid beamforming architecture 100a uses a digital baseband precoder 102 inputted with a plurality of data streams ( ), a plurality of RF chains (referred to herein and after as RF chains "104"), and an analog RF precoder 106 coupled with a plurality of antenna elements, (referred to herein and after as antenna elements "108"). Figure 1B, which is part of 100a, shows an overview of 100b of the analog RF precoder 106. As shown in Figure 1B, each of the plurality of antenna elements 108 in the analog RF precoder 106 is equipped with a plurality of analog phase shifters 110. The plurality of analog phase shifters 110 adjusts the phase of the transmitted or received signal. Such a setup permits the plurality of antenna elements 108 to steer beams in specific directions by controlling the relative phase of signals across the array. When the plurality of analog phase shifters 110 is combined with digital precoders can form beams more precisely toward desired targets. The digital precoders shape the signal in the digital domain. However, certain limitations arise. However, a key limitation arises because the plurality of analog phase shifters 110 operating in the time domain applies the same phase shift across all frequencies, which results in a frequency-flat response. Such uniformity restricts the analog RF precoder's 106 ability to adapt beam shapes for different frequency components, which is especially problematic in wideband communication systems. In contrast, fully digital precoding offers greater flexibility by assigning a dedicated RF chain to each antenna element 108, allowing independent control over both amplitude and phase for each frequency component.

[0062] Nevertheless, the analog beamforming, while cost-effective, faces　limitations in flexibility and scalability. For example, the analog beamforming struggles to implement advanced beamforming techniques, support multiple data streams, and fine-tune beams effectively. Additionally, phase synchronization across the plurality of antenna elements 108 becomes challenging with larger systems, and environmental factors like obstructions can significantly impact the performance. To address the limitations of the analog beamforming while avoiding the complexity and cost of fully digital systems, a new hybrid architecture called Joint Phase Time Arrays (JPTA) has been developed. Further, the conventional hybrid beamforming is explained in the forthcoming paragraphs while explaining Figures 1D and 1E.

[0063] Figure 1Cillustrates a JPTA architecture 100c. As shown, the JPTA uses the plurality of analog phase shifters 110 (Nt) in combination with delay units such as true time delay (TTD) elements ( ) 112, which range from produce frequency-dependent beamforming. The frequency-dependent beamforming permits the JPTA architecture 100c to steer different frequency sub-bands in different spatial directions simultaneously. As referred to in Figure 1C, the JPTA architecture 100c has antenna elements 108, placed spaced apart. The antenna elements 108 are connected to a single RF antenna via the analog phase shifters 110 and N TTD elements ( ) 112, such that N is less than . The matrix (P) 114 maps N delays to analog phase shifters 110. Each row of the matrix (P) 114 has only one non-zero element. Further, the ith row of the matrix (P) 114 determines which of the N TTD elements ( ) 112 is connected to ith antenna 108. The TTD elements ( ) 112 are assumed to be configurable, with a delay variation range of , where is a design parameter to be selected. The plurality of analog phase shifters 110 is assumed to have unit magnitude. Additionally, the plurality of analog phase shifters 110 has a reconfigurable phase in the range . Orthogonal Frequency Division Multiplexing (OFDM) transmission is assumed in the uplink and downlink directions.

[0064] Assuming a single RF chain 104, the 1 downlink Tx signal on kth sub-carrier is given by [equation 1] below:

[0065] [equation 1]

[0066]

[0067] where represents a modulation symbol on kth sub-carrier, represents the digital baseband precoder 102 applied to kth sub-carrier, represents a delay of ith TTD element 112, represents a phase shift introduced by the jth analog phase shifter 110. Furthermore, T represents a diagonal matrix. The diagonal elements are the phases introduced by the plurality of analog phase shifters 110 and represents the vector that captures the delay introduced by the TTD elements 112.

[0068] The effective downlink unit-norm analog beamformer on kth sub-carrier is given by [equation 2]:

[0069] [equation 2]

[0070]

[0071] The same analog beamformer is also applicable at a base station (BS) for the uplink scenario. A beamforming gain, which is a function of frequency, on kth sub-carrier is given by [equation 3]:

[0072] [equation 3]

[0073]

[0074] The JPTA enhances beamforming capabilities by jointly optimizing phase and timing across the plurality of antenna elements 108, enabling more dynamic and frequency-dependent beam control.

[0075] Figures 1Dand1Eillustrate conventional hybrid beamforming. In the hybrid beamforming architecture 100a (as shown in Figure 1A-1B), the analog beamforming is typically implemented using the BS 116 (as shown in Figure 1D). Figure 1E shows time-frequency resource allocation to users (or User Equipment referred to herein and after as "UEs 118") in the hybrid beamforming architecture 100a. As referred to in Figure 1E, one user, such as 118a may be served in one time slot, since the hybrid beamforming architecture 100a may not create multiple beams serving multiple users simultaneously in a given time slot. The plurality of analog phase shifters 110 used in the hybrid beamforming architecture 100a applies fixed or quantized phase adjustments to the RF signals at each antenna element 108. In reference to Figure 1D, the hybrid beamforming architecture 100a allows the formation of a single directional beam, at a time T, that spans the entire frequency band, but the formation of the single directional beam comes with notable limitations. However, since the analog RF precoder 106 lacks frequency selectivity and fine-grained control, multiple independent beams cannot be generated across different frequencies or users simultaneously. As a result, in the downlink, the UEs 118 must be served sequentially using Time Division Duplexing (TDD), where each UE is allocated a specific time slot, as referred to in Figure 1E. As shown, the 118a may be allocated the time slot T1, the 118b may be allocated the time slot T2,the 118c may be allocated the time slot T3,andthe 118d may be allocated the time slot T4. Similarly, in the uplink, the UEs 118 must be scheduled in different time intervals, as multiple beams cannot be formed simultaneously in the hybrid beamforming architecture 100a. Hence, the hybrid beamforming architecture 100a is restricted in its ability to transmit concurrently. This restriction results in a reduction in the overall efficiency of a conventional analog beamforming system. Moreover, to generate N independent beams simultaneously, the analog beamforming system would require N separate RF chains 104, each capable of driving the beam. However, at the mmWave frequencies, the RF chains become impractical due to the high-power consumption and physical constraints associated with integrating a large number of RF chains 104. Such limitation underscores the trade-off in conventional hybrid beamforming, while reducing hardware complexity as compared to the fully digital systems, the conventional hybrid beamforming also constrains the system's ability to support multi-user, multi-beam operations, especially in dynamic or high-density environments.

[0076] Figures 1Fand1Gillustrate the JPTA. The JPTA overcomes the limitations of conventional analog RF precoders 106. Unlike traditional systems that generate a single, frequency-flat beam using only the plurality of analog phase shifters 110, the JPTA enables the formation of multiple frequency-dependent beams. Figure 1F shows that the BS 116 may create four beams simultaneously serving four users. Figure 1G shows time-frequency resource allocation to the users in JPTA systems. Figure 1G shows that all the UEs 118 can be served in a given time slot, since the JPTA systems are capable of creating multiple beams serving multiple users simultaneously. For example, as shown, all the UEs 118 ( 118a, 118b, 118c, and 118d) are scheduled in all the time slots, i.e., T1,T2,T3,andT4.The JPTA is particularly advantageous in mmWave and THz communication systems, where wide bandwidths and high user density demand more flexible and efficient beamforming strategies. One of the most compelling advantages of JPTA is generating N independent beams using fewer than N RF chains 104, which drastically reduces hardware complexity and power consumption, which are critical factors at high frequencies.

[0077] Figures 1H,1I,and1Jillustrate the two-beam case simulation. In the present configuration of the two-beam case, the JPTA with two beams (that is, beam 1 and beam 2) corresponding to user 1 (or ) and user 2(or ), with each beam covering a 400 MHz bandwidth, are considered. As referred to in Figure 1I, the 400 MHz bandwidth is aggregated with four component carriers (CC), each 100 MHz in one beam. Each CC has 66 RBs available for PUSCH transmission, and the remaining RBs are left as guard bands. The beams point in 0oand 5odirections. It is assumed that the UEs 118 are located in the maximum beam gain direction. The link level evaluations assume that the UEs 118 transmit on all the available RBs (66 4 = 264).

[0078] Figure 1Iillustrates a graph depicting beamforming gain as a function of frequency for the JPTA and conventional analog beamformer. In the hybrid beamforming architecture 100a, a Phased Antenna Array (PAA) architecture relies solely on the plurality of analog phase shifters 110 for analog beamforming. The analog beamforming results in the generation of frequency-flat beams, meaning each beam maintains a consistent gain across the entire bandwidth. For example, as illustrated in Figure 1I, two beams, each spanning 400 MHz, can be produced using two separate RF chains 104, with their peak gains directed at 0oand 5orespectively. However, if only a single RF chain 104 is available, these beams must be generated in different time slots using Time Division Duplexing (TDD), as the PAA cannot support simultaneous multi-beam transmission with the single RF chain 104. Such a limitation restricts spectral efficiency and user scheduling flexibility. In contrast, the JPTA enables the creation of frequency-dependent beams, allowing multiple beams to be formed simultaneously across different frequency bands, even with the single RF chain 104. As shown in Figure 1I, the JPTA can produce two beams concurrently, each occupying a distinct frequency band. However, such capability introduces a trade-off that is the beam gains in the JPTA are frequency-selective, that is, the JPTA varies across the bandwidth. The variation in bandwidth can lead to performance degradation, particularly at the band edges, where the gain tends to drop. These frequency-selective characteristics are modelled and evaluated using a link-level simulator (LLS) to assess their impact on the performance of the communication system.

[0079] In the uplink scenario, when the BS 116 is equipped with the JPTA using the single RF chain 104, the received signal on kth sub-carrier can be modelled as given in [equation 4]:

[0080] [equation 4]

[0081]

[0082] where represents a channel gain, represents a frequency-selective beam gain introduced by the JPTA, represents a transmitted signal, and n represents an additive noise. To isolate and study the impact of the frequency-selective nature of the JPTA beamforming, the analysis assumes an Additive White Gaussian Noise (AWGN) channel with for all k, effectively removing channel variability from the [equation 4]. For quantification, a link-level simulator (LLS) is used to model the frequency-selective beam gains and assess their impact on Block Error Rate (BLER) performance. Two configurations are considered, that is, a two-beam case and a four-beam case. In the two-beam case, an 800 MHz total bandwidth is divided into two 400 MHz beams serving two UEs 118. The two-beam case is explained in the upcoming paragraphs while explaining Figures 1H-1J. In the four-beam case, a 400 MHz bandwidth is split into four 100a MHz beams for four UEs 118. The four-beam case is explained in the upcoming paragraphs while explaining Figures 1L-1N. Simulation results (as shown in Figure 1I-1J and 1L-1M) reveal that the frequency selectivity of JPTA beam gains leads to performance degradation compared to the PAA, which offers flat beam gains across the band. The degradation ranges from approximately 0.6 to 1.5 dB, depending on the number of beams and the Modulation and Coding Scheme (MCS) used. Notably, higher MCS levels, which are more sensitive to signal quality, experience greater performance loss due to reduced beam gain at the band edges. Despite such a drawback, the JPTA's ability to support simultaneous multi-user transmission with fewer RF chains 104 remains a compelling advantage for future 6G systems, where spectral efficiency and hardware scalability are critical.

[0083] Referring to Figure 1J, the BLER vs Signal-to-Noise Ratio (SNR) plot shows BLER of PAA, JPTA beam 1 (CC1-CC4) corresponding to user 1 (or ), and JPTA beam 2 (CC5-CC8) corresponding to user 2 (or ),in AWGN channel. From the BLER vs the SNR plot as shown in Figure 1J, there is ~0.6 dB SNR degradation in the case of JPTA compared with the case of PAA, which is due to the frequency-selective beam gains in the JPTA. In the case of the JPTA, the beams are produced simultaneously using one RF chain 104, whereas the PAA requires two RF chains 104 to produce two beams, that is, the beam 1 and the beam 2, simultaneously. As depicted in Figure 1K, there is a SNR loss of 0.6 dB.

[0084] Figures 1K,1L,and1Millustrate a four-beam case simulation. The JPTA with four beams, that is, beam 1, beam 2, beam 3, and beam 4, corresponding to are considered. As referred to in Figure 1K, each beam spans a 100a MHz bandwidth corresponding to 1 CC. Within each CC, 66 RBs are allocated for Physical Uplink Shared Channel (PUSCH) transmission, while the remaining RBs serve as guard bands. The beam 1, beam 2, beam 3, and beam 4 are directed toward angles of , with the users (or UEs 118) assumed to be positioned at the peak gain direction of each beam. The UEs 118 are assumed to be located in the maximum beam gain direction. The link-level evaluations assume that the UEs 118 transmit on all the available RBs (66 RBs). The resulting BLER vs SNR plot compares the performance of the conventional PAA with that of JPTA beam 1 and beam 2, each covering CC1 and CC2, respectively, under the AWGN channel. Similarly, beam 3 and beam 4 cover CC3 and CC4, respectively. The analysis (as shown in Figure 1M) reveals an approximate 1 dB SNR degradation in the JPTA case relative to the PAA. Notably, the JPTA achieves simultaneous multi-beam transmission using a single RF chain 104, whereas PAA requires four RF chains to produce just two beams concurrently. Figure 1L shows four JPTA beams, each covering a bandwidth of 100 MHz. In the case of JPTA, these four beams can be simultaneously created using a single RF chain and can be used to serve four UEs 118, simultaneously. The plot, as illustrated in Figure 1M, also shows frequency-flat beams corresponding to the conventional hybrid beamforming architecture 100a. These beams cannot be produced simultaneously using the separate RF chain, but need to be created in TDD fashion. Further, Figure 1M depicts the trade-off resulting in a modest 1 dB SNR loss in the evaluated configuration.

[0085] Figures 1Nand1Oillustrate a link-level simulation of the four-beam case and the two-beam case, respectively. The results corresponding to the two-UE case and the four-UE case may differ since the beam gains are different in both cases. However, the common trend amongst the two UEs case and the four UEs case is due to the increased performance loss with higher MCS levels. Figures 1N and 1O show a performance comparison between the PAA and the JPTA in terms of achieving a 10% BLER as a function of MCS value. As shown in Figures 1N and 1O, as the MCS value increases, a notable widening in the SNR gap between PAA and JPTA becomes evident. The SNR gap indicates that JPTA, which introduces frequency-selective beam gains, suffers from increased performance degradation at higher MCS levels. These higher MCS values typically correspond to higher data rates but are also more sensitive to channel impairments. The frequency-selective nature of JPTA's beamforming results in variations in gain across different frequency components, thereby impacting the communication system's ability to maintain a reliable link under challenging conditions. In contrast, the PAA tends to provide more uniform gain characteristics, making it more robust, especially at higher MCS levels. Consequently, the performance loss associated with the JPTA relative to the PAA becomes more pronounced as the MCS increases, underscoring the importance of considering modulation and coding strategies when deploying beamforming techniques like the JPTA in frequency-selective channels.

[0086] Figure 1Pillustrates a graphical representation of beam gain and frequency. As shown, the beam gain pattern of JPTA reveals that certain RBs in the mid-frequency band exhibit higher beam gains, while the gains gradually decrease toward the band edges. Transmitting on high beam gain RBs can reduce performance loss. Hence, determining the RB allocation and the MCS based on the estimated SNR is crucial, such that the performance loss due to JPTA frequency-selective beam gains is minimized and improved throughput is achieved. Thus, there is a requirement for physical RB allocation and MCS determination in JPTA systems to overcome the above-mentioned challenges.

[0087] Therefore, there is a need for enhanced techniques to address the above-mentioned deficiencies.

[0088] The present disclosure provides a method and a system to address the performance degradation issue resulting from frequency-selective beamforming gains in a Joint Phase Time Arrays (JPTA) wireless communication system. In particular, the disclosed method and system take a Signal-to-Noise Ratio (SNR) of a User Equipment (UE) (interchangeably referred to as "a user"), as input to provide a plurality of Physical Resource Blocks (PRBs), PRB indices, and a modulation and coding scheme (MCS) value to be used. The plurality of PRBs may be interchangeably referred to as the plurality of resource blocks (RBs), and the PRB indices may be interchangeably referred to as the RB indices. The disclosed method and system minimize the performance degradation due to frequency-selective beam-gain and enhance the throughput. The disclosed method and system provide as high as 100% throughput gain in a low SNR regime and as high as 38% gain in a medium SNR regime. Furthermore, the present disclosure also provides the changes needed in a scheduler to incorporate the smart RB allocation.

[0089] Figure 2illustrates an exemplary environment 200 of a Joint Phase Time Arrays (JPTA) wireless communication system for the implementation of a system 210 to optimize resource allocation, according to an embodiment of the present disclosure.

[0090] In an exemplary embodiment, the environment 200 of the JPTA wireless communication system may include at least one Base Station (BS) 204 in communication with a plurality of UEs 218a-218n via one or more networks 202 (e.g., Radio technology). In an implementation, the BS 204 may communicate with the one or more networks 202, such as the Internet, a proprietary Internet Protocol (IP) network, or another data network. In a non-limiting example, the plurality of UEs 218a-218n may be interchangeably referred to herein and after as "the UEs 218". In an implementation, the UEs 218 may be a mobile device, such as a cell phone, a wireless laptop, a wireless PDA, or the like.

[0091] In an embodiment, the BS 204 may be designed as a sophisticated communication node that may optimally schedule and transmit data to the plurality of UEs 218. The BS 204 may include a processing unit (not shown in the Figure) that may perform several critical tasks to efficiently enhance the wireless communication. The BS 204 may provide wireless broadband access to the　one or more networks 202 for the UE within a coverage area 220 of the BS 204. In some embodiments, the BS 204 may communicate with the UE using Fifth Generation (5G) / New Radio (NR), long-term evolution (LTE), LTE-advanced (LTE-A), WiMAX, Wi-Fi, or other wireless communication techniques. In a non-limiting example, the JPTA wireless communication system may operate using a 6thGeneration (6G) wireless communication network. The BS 204 may include a system 210 to optimize resource allocation in the JPTA wireless communication system. In another embodiment, the system 210 may be connected to the BS 204 within the JPTA wireless communication system.

[0092] In an embodiment, the system 210 may include at least a processor 212, a memory 214, a data unit 216, and a transceiver 217. The system 210 may be configured to determine the number of the RBs to be allocated to each of the UEs 218, the RB indices to be allocated, and the MCS value to be assigned to each of the UEs 218 to improve the performance. In an implementation, the RB indices may help in organizing and managing frequency-time resources within a carrier bandwidth. The RB indices serve as numerical identifiers for each RB, allowing the scheduler to efficiently assign specific blocks for uplink or downlink transmission. For instance, in a 20 MHz carrier using 15 kHz subcarrier spacing, the system 210 may accommodate 100 RBs, indexed sequentially from 0 to 99. The structured indexing enables precise and non-overlapping allocation of resources to multiple users, facilitating dynamic scheduling and minimizing interference. The system 210 may include a computation of the SNR on each RB of the plurality of RBs based on the received wideband SNR estimate and JPTA beam gains. The system 210 may compute throughput for each possible number of the plurality of RBs and MCS value using an Exponential Effective SNR mapping (EESM) based on the computation of the SNR per RB. The plurality of RB allocation may be considered starting from the RB with the highest beam gain, and may further proceed in a descending order of the beam gains with the help of a smart RB allocation procedure. Further, a look-up table may be used by the system 210 to map the SNR to the optimal number of the plurality of RBs, and, accordingly, an optimal MCS value may be constructed. In an implementation, the system 210 may use the look-up table as is or with a slight modification to determine RB allocation, RB indices, and MCS value for each of the UEs 218 based on the UE's SNR. The system 210 may perform a modification in a scheduler (not shown) that may be required for the implementation of RB allocation in the JPTA wireless communication systems. In a non-limiting example, the system 210 may function as the scheduler.

[0093] In an embodiment, the processor 212 may be in communication with the memory 214. The processor 212 may be configured to execute instructions stored in the memory 214 and to perform various processes for optimizing resource allocation in the JPTA wireless communication system, as discussed throughout the disclosure. The processor 212 may be configured to initiate or stop one or more routines or a process based on the SNR of each RB. The processor 212 may be a single processing unit or several units, all of which could include multiple computing units. The processor 212 may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors (DSPs), central processing units (CPUs), an application processor (AP), or like, a graphics-only processing unit such as a graphics processing unit (GPU), a visual processing unit (VPU), and / or an Artificial intelligence (AI) dedicated processor such as a neural processing unit (NPU), state machines, logic circuitries, and / or any devices that manipulate signals based on operational instructions. Among other capabilities, the processor 212 may be configured to fetch and execute computer-readable instructions and data stored in the memory 214.

[0094] In an embodiment, the data unit 216, amongst other things, includes routines, programs, objects, components, data structures, etc., which perform particular tasks or implement data types. The data unit 216 may be implemented as signal processor(s), state machine(s), logic circuits, or other devices / components that manipulate signals based on operational instructions. Further, the data unit 216 may be implemented in hardware, instructions executed by a processing unit, or by a combination thereof. In another embodiment of the present disclosure, the data unit 126 may be machine-readable instructions (software) that, when executed by the processor 212, perform any of the described functionalities.

[0095] In an embodiment, the transceiver 217 may be employed for bidirectional communication across the wireless networks. The transceiver 217 may integrate both transmission and reception capabilities within a unified hardware and software framework of the system 210. The transceiver 217 may facilitate real-time signal processing, adaptive modulation, and dynamic frequency management. Furthermore, the transceiver 217 may incorporate features such as automatic gain control, error correction, and multi-band compatibility to ensure robust data exchange across varying environmental and network conditions. Additionally, the transceiver 217 may enhance resource allocation efficiency within the JPTA. The transceiver 217 may integrate adaptive phase control and dynamic time-slot scheduling to facilitate optimized transmission and reception across multidimensional antenna arrays. Through real-time channel feedback and predictive signal processing, the transceiver 217 may coordinate spatial beamforming and temporal access to minimize interference, balance power usage, and maximize throughput.

[0096] In an embodiment, the processor 212 may be configured to create a sorted RB list based on frequency-selective beam gains of the plurality of RBs. The sorted RB list may include the plurality of RBs in a descending order based on the corresponding frequency-selective beam gain. In a non-limiting example, the numbers of possible RBs and MCS values may be swept over. For instance, when one UE, such as 218a, from among the UEs 218, is scheduled per beam, the RB indices may be determined based on allocating the RBs with the highest beam gains to the 218a. The RBs may be sorted in descending order of beam gains, and the sorted order may be further stored based on the condition that is, if jth UE is allocated RBs, then first RBs in the sorted list of RBs may be allocated to the 218a. A use-case scenario when one UE is scheduled per beam is explained in the forthcoming paragraphs in reference to Figures 7a and 7b.

[0097] The processor 212 may be configured to calculate the SNR for each RB of the plurality of RBs in the sorted RB list, based on a wideband SNR corresponding to one of the UEs 218a-218n and frequency-selective beam gain corresponding to the RB. The processor 212 may be configured to compute a throughput value for each of a combination of one or more calculated SNRs corresponding to the plurality of RBs and for associated MCS values corresponding to the plurality of RBs. In a non-limiting example, for a given wideband UE SNR, the EESM, spectral efficiency, and the throughput value may be computed. In an implementation, the processor 212 may be configured to compute the throughput value using one of the EESM techniques, a Mean Mutual Information per Symbol (MMIS) technique, and a Received Bit Information Rate (RBIR) technique. Furthermore, the processor 212 may be configured to determine an optimal MCS value and an optimal number of RBs for each of the plurality of UEs 218 based on the computed throughput value and the wideband SNR for the corresponding UE. In a non-limiting example, the number of RBs may be, and the MCS value selected to maximize the throughput value. Furthermore, an optimum number of the RBs and an optimum MCS value for a given SNR may be stored in the look-up table. An example of the look-up table is shown below in [Table 1]:

[0098] SNR (dB)Optimal no. RBsOptimal MCS-4153-3164-2174-12040394

[0099] In an implementation, the BS 204 may use the look-up table to determine the optimum number of RBs and the optimum MCS value. The processor 212 may be further configured to generate a mapping of the wideband SNR to the optimal number of RBs and the corresponding optimal MCS value.

[0100] The processor 212 may be further configured to allocate at least one of the number of RBs, the corresponding RB indices, and the corresponding MCS value to the one or more UEs, such as the 218a, the 218b, the 218c, among the plurality of UEs 218a-218n, using the mapping. The mapping may further include a plurality of RB indices corresponding to the optimal number of RBs. In an implementation, the processor 212 is configured to allocate the at least one of the number of RBs, the corresponding RB indices, and the corresponding MCS value for the one or more UEs among the plurality of UEs 218. The process for determining the number of JPTA beams to be used is explained in the forthcoming paragraphs in reference to Figure 3 and Figure 4. The processor 212 may be further configured to schedule the one or more UEs based on the optimal number of RBs corresponding to the one or more UEs. The at least one of the number of RBs, the corresponding RB indices, and the corresponding MCS value may be allocated for the corresponding scheduled one or more UEs using the mapping.

[0101] In another implementation, the processor 212 may be configured to allocate the at least one of the number of RBs, the corresponding RB indices, and the corresponding MCS value when the number of UEs is more than two for a beam among a plurality of beams in the JPTA wireless communication system. The processor 212 may be further configured to allocate one or more RBs associated with a first frequency range to the one or more UEs among the plurality of UEs 218 with corresponding SNR below a predefined threshold. The one or more RBs associated with the first frequency range may have beam gain values more than or equal to a predefined beam gain threshold. In an embodiment, the predefined beam gain threshold may be pre-configured or user-defined. Furthermore, the processor 212 may be configured to allocate one or more RBs associated with a second frequency range, with beam gain values less than the predefined beam gain threshold, to the one or more UEs among the plurality of UEs 218 with corresponding SNR above the predefined threshold.

[0102] In an implementation, the processor 212 may be configured to allocate the at least one of the number of RBs, the corresponding RB indices, and the corresponding MCS value to the one or more UEs for an uplink communication and a downlink communication.

[0103] In an aspect, strategically allocating the optimal number of high-gain RBs may yield substantial performance benefits, particularly in a very low SNR regime. For instance, the proper allocation of the optimal number of high-gain RBs may result in up to 100% average throughput gain in a very low SNR regime, when one UE, such as the UE 218a from among the plurality of UEs 218, is scheduled per Component Carrier (CC). Furthermore, the allocation of the optimal number of high-gain RBs to determine an optimal number of the RBs, the RB indices, and the MCS may not be employed every time the UE 218a is scheduled. Thus, the allocation of the optimal number of high-gain RBs may not need to be executed dynamically with every scheduling instance. Instead, the RBs may be performed offline, and the look-up table with SNR values and the corresponding optimum number of RBs and MCS values may be stored in the memory 214. Furthermore, each time the UE 218a is scheduled, the stored look-up table, as referred to in [Table 1], may be looked up for fetching the optimal number of RBs and the MCS value. In an implementation, during real-time scheduling, the system 210 may refer to the look-up table to retrieve best-fit parameters for the UE 218a, thereby reducing computational overhead while maintaining high throughput efficiency. Such an approach may streamline the scheduling operations and ensure consistent performance across varying channel conditions.

[0104] In an implementation, to incorporate the proper RB allocation and MCS determination, the modification in the implementation of the system 210 may be performed. The system 210 may be used for performing scheduling of the one or more UEs per CC, based upon which the allocation of the RBs may be performed for one / two / more than two UEs per CC. The process for scheduling the UEs 218 on ith JPTA beam is explained in the forthcoming paragraphs in reference to Figure 5.

[0105] Figure 3illustrates a process flow 300 of the system 210 for determining the number of JPTA beams to be used, according to an embodiment of the present disclosure.

[0106] In an implementation, at operation 302, the system 210 may initiate the process 300 to incorporate the proper RB allocation and MCS determination.

[0107] At operation 304, the system 210 may determine the number of JPTA beams and select the corresponding beam identifiers (IDs). For instance, in case a maximum of four JPTA beams are allowed by the system 210, the JPTA beams less than four may also be used in a particular scheduling instance.

[0108] At operation 306, upon determining the number of JPTA beams, a first JPTA beam may be considered to schedule the one or more UEs on the first JPTA beam.

[0109] At operation 308, the system 210 may schedule the one or more UEs on the first JPTA beam.

[0110] Operations 306 and 308 may iterate till the UEs 218 on each of the JPTA beams are considered.

[0111] At operation 310, once the UEs 218 are scheduled on all the JPTA beams, the system 210 may determine the RB indices and the MCS for each of the scheduled UEs 218.

[0112] At operation 312, the process 300 ends.

[0113] Such a configuration step may ensure optimal spatial coverage and the RB allocation based on network conditions and user distribution. Once the JPTA beam is established, the system 210 may proceed to assign the one or more UEs to each configured JPTA beam. Such allocation may consider factors such as, but not limited to, signal strength, user demand, and interference levels to maximize connectivity and throughput. After all of the one or more UEs are successfully assigned across the JPTA beams, the system 210 may refine the RBs allocation by selecting appropriate RB indices for each UE, which may define the specific time-frequency allocations. Simultaneously, the system 210 may determine the MCS value tailored to each of the one or more UEs' channel quality, balancing data rate and reliability to achieve efficient communication.

[0114] Figure 4illustrates a process flow 400 of the system 210 for determining the number of JPTA beams to be used,according to an embodiment of the present disclosure.

[0115] In an embodiment, at operation 402, may initiate the process 400 to the system 210 may be adapted to determine the number of JPTA beams to be used.

[0116] At operation 404, the system 210 may be adapted to determine a primary UE based on the proportional fair (PF) metric of all the UEs 218 that may be active. The PF metric may be used to strike to balance between maximizing total throughput and ensuring fairness among the plurality of UEs 218. The PF metric may be computed for the plurality of UEs 218 by assuming the maximum supported uplink bandwidth for the plurality of UEs 218. In an implementation, for the plurality of UEs 218, the BS 204 may decide which one of the plurality of UEs 218 may transmit. The PF metric for each UE may be calculated, and the UEs with the highest metric, referred to as "a primary UE" may be selected to transmit the data.

[0117] At operation 406, the system 210 may be adapted to calculate the elevation angle for the primary UE. The primary UE with the same elevation angle, referred to as "A", may be counted. Further, the maximum number of JPTA beams allowed, referred to as "B", may be identified. A minimum of "A" and "B" may be the number of JPTA beams (nJPTABeams) to be used for scheduling.

[0118] At operation 406, the system 210 may be adapted to obtain a list of the JPTA beams used for scheduling (ListofJPTABeams). Further, to obtain the list of the JPTA beams used, primary UE's beam identifiers (IDs) may be added to theListofJPTABeamsand the remaining (nJptaBeams-1) beams may be added to the list, by selecting the beams serving the plurality of UEs 218a-218n with a highest PF metrics. In a non-limiting example, the first beam inListofJPTABeamsmay always be the primary UE's beam.

[0119] At operation 406, the system 210 may be adapted to determine total bandwidth (Total uplink BW) covered by each JPTA beam based onnJptaBeams.Once a total bandwidth is identified, the bandwidth corresponding to each beam may be calculated by dividing the total bandwidth by the number of JPTA beams. In an implementation, the system 210 may determine the bandwidth covered by each JPTA beam ( ) as given below in [equation 5]:

[0120] [equation 5]

[0121]

[0122] Figure 5illustrates a process flow 500 of the system 210 for scheduling the UEs 218 on ith JPTA beam, according to an embodiment of the present disclosure.

[0123] At operation 502, the system 210 may initiate a process 500 for scheduling the UE on the ith JPTA beam.

[0124] At operation 504, the system 210 may be adapted to select the first UE 218 to be scheduled on ith JPTA beam. From the list of active UEs for the ith JPTA beam, a number of resource block groups (RBGs) may be calculated by the system 210 to be allocated to each UE. Further, the number of RBGs to be allocated to jth UE may be calculated as given in [equation 6] below:

[0125] [equation 6]

[0126]

[0127] Where K represents the maximum number of RBs that may be allocated to each UE, represents a required number of RBs for each UE based on a buffer status report, which may be calculated for each UE assuming the mean / median of the JPTA beam gain. Further, the represents a maximum number of RBs that may be allocated based on the power control. The may be calculated for each UE, assuming the mean / median of the JPTA beam gain. Further, represents the optimum number of RBs from the look-up table. Furthermore, the rate for each user ( ) may be calculated based on . In an implementation, the MCS value corresponding to the UE's SNR may be used for the computation of .The may be further used for computation of the PF metric for each UE ( ). The user with the highest PF metric may be selected for scheduling, and the selected UE ID may be added to the list of scheduled UEs. The selected user may be removed from the list of active UEs for the ith JPTA beam.

[0128] At operation 506, the system 210 may be adapted to determine if additional UEs may be scheduled on the same JPTA beam or not. In an implementation, the additional UEs may be scheduled on the same JPTA beam when the bandwidth on the ith JPTA beam may be remaining, and the UEs may be available on the ith JPTA beam.

[0129] At operation 508, the system 210 may be adapted to determine subsequent UEs to be scheduled on ith JPTA beam. To determine subsequent UEs to be scheduled, the number of RBGs to be allocated may be calculated for the plurality of UEs 218 in the list of active UEs for ith JPTA beam. Further, the number of RBGs to be allocated to the jth UE may be calculated using [equation 7] as given below:

[0130] [equation 7]

[0131]

[0132] where P denotes the total of all the RBs allocated to the scheduled UEs, may be obtained from the stored look-up table. The may be the optimal RB corresponding to a modified SNR value, denoted by , that may be computed using the actual SNR value of ith UE. The modified SNR value may be computed based on the stored look-up table. The stored look-up table may provide the optimal number of RBs to be allocated, assuming that the allotment initiates from the RBs with the highest beam gains. The assumption may not be correct when more than one UE on the JPTA beam exists. Therefore, the SNR may be modified and used to determine the number of RBs from the look-up table. The modified SNR may be obtained using [equation 8] as given below:

[0133] [equation 8]

[0134]

[0135] where denotes the JPTA beam gains averaged over P RBs with the highest beam gains.

[0136] The process 500 may be repeated for computing the rate and the PF metric for each UE. The system 210 may compute the rate based on the MCS value corresponding to the UE's modified SNR from the look-up table (that is, [Table 1]). The UE with the highest PF metric may be selected to be added to the list of scheduled UEs. Further, the selected UE may be removed from the active UE list.

[0137] At operation 510, if an additional UE is not scheduled on the same JPTA beam at operation 506, the process 500 may end.

[0138] Figure 6illustrates a process flow 600 of the system 210 for determining the RB indices and MCS for each scheduled UE, according to an embodiment of the present disclosure.

[0139] At operation 602, the system 210 may initiate the process 600 for determining the RB indices and MCS for each scheduled UE.

[0140] At operation 604, the system 210 may be adapted to check the number of scheduled UEs for each beam inListofJptaBeams.

[0141] At operation 606, when the number of UEs scheduled on theith JPTA beam is 1, procedure 1 (P1) at operation 608 may be followed for determining the RB indices and MCS value to be assigned.

[0142] At operation 612, when the number of UEs scheduled on theith JPTA beam is not 1, rather the number of UEs scheduled on theith JPTA beam is 2, that is, two UEs are scheduled for a given beam, procedure 2 (P2) at operation 614 may be used for determining RB indices and MCS value. A use-case scenario when the two UEs are scheduled per beam is explained in the forthcoming paragraphs in reference to Figures 8a and 8b.

[0143] At operation 616, when the number of UEs scheduled on theith JPTA beam is not 2, but the number of UEs scheduled on theith JPTA beam is more than 2, procedure 3 (P3) at operation 618 may be used for determining RB indices and MCS value. A use-case scenario when more than two UEs are scheduled per beam is explained in the forthcoming paragraphs in reference to Figures 9a and 9b.

[0144] At operation 620, when one of the procedures P1, P2, or P3 is followed, the beam next to theith beam (that is, the beam corresponding to i+1) may be used for scheduling.

[0145] At operation 622, the process 600 may end when all the JPTA beams are considered for scheduling.

[0146] Figure 7aillustrates a use case scenario illustrating the scheduling of one UE per beam in the JPTA wireless communication system, in accordance with the present disclosure.

[0147] Figure 7billustrates a graphical representation of a beam gain with frequency when one UE is scheduled per beam, in accordance with the present disclosure.

[0148] Referring to Figure 7a, when one UE, such as UE 218a, is scheduled per beam, the RB indices may be determined based on allocating the RBs with the highest beam gains to the scheduled UE. The RBs may be sorted in descending order of beam gains, and the sorted order may be further stored based on the condition that is, if jth UE is allocated PjRBs, then first RBs in the sorted list of RBs may be allocated to the UE 218a.

[0149] The MCS value may be obtained from the look-up table. In an implementation, the obtained MCS value may not be the optimal MCS because the allocated number of RBs is and not . Therefore, the MCS value may be modified by initializing a variable j=0, which represents maxMCSValue, and computing the EESM based on the UE's SNR and allocated RBs, SE, and throughput to select the optimal MCS value that may maximize the throughput. Referring to Figure 7b, as shown, the beam gain pattern of JPTA reveals that certain RBs in the mid-frequency band, that is, at frequency , exhibit higher beam gains, while the gains gradually decrease toward the band edges, that is, at frequency ( ) and ( ). Accordingly, the UEa218a is allocated the RBs in the mid-frequency band. Thus, Figure 7a illustrates the case where only a single user may be scheduled on the given JPTA beam, whereas Figure 7b illustrates a manner in which the RBs may be allocated when only a single user may be scheduled per JPTA beam (as depicted in Figure 7a).

[0150] Figure 8aillustrates a use case scenario illustrating the scheduling of two UEs per beam in the JPTA wireless communication system, in accordance with the present disclosure.

[0151] Figure 8billustrates a graphical representation of a beam gain with frequency when two UEs are scheduled per beam, in accordance with the present disclosure.

[0152] Referring to Figure 8a, when more than one UE, such as UEs 218a, 218b, are scheduled per beam, an additional constraint for the RB allocation may arise. In an implementation, contiguous RBs may be allocated to every UE among the UEs 218a, 218b. In a general scenario, the existing Downlink Control Information (DCI) formats may be used to indicate the RB allocation to the UEs 218, which may not support non-contiguous allocation. Therefore, the UEs 218 may be required to be allotted the high beam gain RBs in a contiguous manner, which may be considered a limitation. Hence, to overcome the above limitation, RBs with the highest beam gains, denoted by P, may be used. Starting from the lowest frequency RB in P, the first RBs may be allocated to the and the next may be allocated to the UE2 as shown in Figures 8a and 8b.

[0153] For each of the UEs 218, the MCS value may be selected by initiating a variable i =1:2, and j=0 (for maxMCSValue), and computing the EESM based on the ith UE's SNR and the allocated RBs, SE, and the throughput. Thus, the optimal MCS value may be selected that maximizes the throughput. Referring to Figure 8b, the sum of RBs allocated to the one or more UEs, for example, the 218a and the 218b may be computed. Among the sum RBs with a highest beam gain, the frequency bands may be allocated from the left side of the frequency band, that is , where the may be the maximum frequency. For example, the beam gain is lowest at a frequency , that is, at the left edge of and at frequency , i.e., at the right edge of the . Accordingly, the RBs from to the may be allocated to the 218a. Similarly, RBs from the to ] may be allocated to the 218b. Thus, Figure 8a illustrates the case where two users may be scheduled on the given JPTA beam. Figure 8b illustrates the manner in which the RBs may be allocated when two users are scheduled per JPTA beam (scenario depicted in Fig. 8a).

[0154] Figure 9aillustrates a use case scenario illustrating the scheduling of more than two UEs per beam in the JPTA wireless communication system, in accordance with the present disclosure.Figure 9billustrates a graphical representation of a beam gain with frequency when more than two UEs are scheduled per beam, in accordance with the present disclosure.

[0155] As discussed above about Figures 8a and 8b, when more than one UE is scheduled per beam, the additional constraint of allocating contiguous RBs may arise. When more than two UEs are scheduled per beam, there are two implementations of allocating high beam gain RBs in a contiguous fashion. In an implementation, to determine the RB indices, RBs with the highest beam gains (P) may be used. Starting from the lowest frequency RB in P, the UEs, that is may be allocated contiguous RBs as shown in Figures 8a and 8b, where denotes the total number of scheduled UEs on the ith JPTA beam.

[0156] In reference to the MCS selection, for each UE, the MCS value may be selected by initiating a variable and variable j=0:maxMCSValue, and computing the EESM based on the ith UE's SNR and allocated RBs, SE, and the throughput. Thus, the optimal MCS value may be selected that maximizes the throughput.

[0157] In another implementation, to determine the RB indices, RBs with the highest beam gains may be used, and high beam gain RBs may be allocated to the UEs with low SNR. As discussed earlier, in the low SNR regime, the loss in throughput may be significant and may be as high as 100%. Therefore, allocation of high-gain RBs for the UEs with the low SNR values (< 5 dB) may be considered vital.

[0158] In an implementation, for RB allocation, a set of UEs with SNR greater than the predefined threshold may be selected, for example, SNR=5 dB may be denoted by . Another set of UEs with SNR below the threshold may be added to another set, denoted by . Let the number of UEs in is denoted by n. Starting from the lowest frequency RB in P, contiguous RBs are allocated to the first n / 2 UEs in if n is even. However, contiguous RBs are allocated to the first (n-1) / 2 UEs, if n is odd. The next set of RBs to the UEs in may be allocated in a contiguous fashion. Further, the remaining RBs to the remaining n / 2 (or (n-1) / 2 if n is odd) UEs in may be allocated as shown in Figures 9a and 9b. The four UEs ( ) may be scheduled in a given beam and . Assuming and The RB allocation may be done as shown in Figure 9b. Thus, Figure 9a illustrates the case where four users are scheduled on a given JPTA beam, whereas Figure 9b shows how RBs are allocated when more than two users are scheduled per JPTA beam (scenario depicted in Figure 9a). In an implementation, the predefined threshold corresponding to the SNR of the UEs 218 may be defined. The RBs may be allocated to the UEs 218 based on whether the corresponding SNR is above or below the predefined threshold set for the SNR. The at least one or more UE with the lowest SNR may be allocated the RBs with the highest beam gains.

[0159] Figure 10illustrates an exemplary process flow for a method 1000 for predicting the DCD score, according to an embodiment of the present disclosure.

[0160] In an embodiment, the method 1000 may be a computer-implemented method executed, for example, by the system 210. For the sake of brevity, the constructional and operational features of the system 210 that are already explained in the description of Figure 2, Figure 3, Figure 4, Figure 5, Figure 7, Figure 8, and Figure 9 are not explained in detail in the description of Figure 10.

[0161] At step 1002, the method 1000 may include creating the sorted RB list based on the frequency-selective beam gains of the plurality of RBs. The sorted RB list may include the plurality of RBs in descending order based on the corresponding frequency-selective beam gain.

[0162] At step 1004, the method 1000 may include calculating the SNR for each RB in the sorted RB list, based on the wideband SNR corresponding to the UE among the plurality of UEs 218a-218n and the frequency-selective beam gain corresponding to the RB.

[0163] At step 1006, the method 1000 may include computing the throughput value for each of a combination of one or more calculated SNRs corresponding to the plurality of RBs and for associated MCS values corresponding to the plurality of RBs. In an implementation, the throughput value may be computed using one of the EESM techniques, the MMIS techniques, and the Received Bit Information Rate (RBIR) technique.

[0164] At step 1008, the method 1000 may include determining the optimal MCS value and the optimal number of RBs for each of the plurality of UEs 218 based on the computed throughput value and the wideband SNR for the corresponding UE.

[0165] At step 1010, the method 1000 may include generating the mapping of the wideband SNR to the optimal number of RBs and the corresponding optimal MCS value.

[0166] At step 1012, the method 1000 may include allocating at least one of the number of RBs, the corresponding RB indices, and the corresponding MCS value to one or more UEs among the plurality of UEs 218 using the mapping.

[0167] In an implementation, allocating at step 1012 may further include determining the number of beams to be used for the one or more UEs among the plurality of UEs. The allocation at step 1012 may further include scheduling the one or more UEs based on the optimal number of RBs corresponding to the one or more UEs. Furthermore, the allocation at step 1012 may include allocating the at least one of the number of RBs, corresponding RB indices, and corresponding MCS value for the corresponding scheduled one or more UEs using the mapping. In a non-limiting example, the mapping may further include the plurality of RB indices corresponding to the optimal number of RBs.

[0168] In an implementation, when the number of plurality of UEs is more than two for the beam among the plurality of beams in the JPTA wireless communication system, the at least one of the number of RBs, the corresponding RB indices, and the corresponding MCS value may include allocating one or more RBs associated with the first frequency range. The allocation may be based on the beam gain values that may be more than or equal to the predefined beam gain threshold, to one or more UEs among the plurality of UEs with corresponding SNR below the predefined threshold. Further, the one or more RBs associated with the second frequency range, with beam gain values less than the predefined beam gain threshold, may be allocated to the one or more UEs among the plurality of UEs with corresponding SNR above the predefined threshold.

[0169] In an implementation, allocating at step 1012 may further include allocating the at least one of the number of RBs, corresponding RB indices, and corresponding MCS value to the one or more UEs for the uplink communication and the downlink communication.

[0170] In a non-limiting example, when one UE 218a may be scheduled per beam for scheduling, the one or more parameters may be set as given in [Table 2] below:

[0171] ParameterValueSub-carrier spacing120 kHzCarrier frequency28 GHzNumber of UEs1 UE per carrier component (CC)UE locations Total bandwidth400 MHzBandwidth per JPTA beam100 MHz

[0172] Figure 11illustrates a plot 1100 for SNR versus optimal RBs and MCS, according to an embodiment of the present disclosure.

[0173] Figure 11shows a variation in the optimal number of RBs and the optimal MCS value as a function of the SNR, for the PAA and the JPTA. The pink plot indicates the optimal number of RBs shown on the left axis, and the red plot indicates the optimal MCS, which is shown on the right side of the axis. As shown in Figure 11, beyond 5 dB SNR, all the available RBs (66 RBs in this case) that are allocated may turn out to be optimal. However, in the lower SNR regime (i.e., SNR < 5 dB), using all the available RBs may not result in optimal throughput. Further, using all the 66 RBs in the lower SNR regime may result in performance loss.

[0174] Figures 12a and 12billustrate plot 1200 of SNR versus maximum achievable throughput for PAA and JPTA corresponding to four UEs with optimal RB allocation and full band allocation, according to an embodiment of the present disclosure.

[0175] Referring to Figures 12a and 12b, when the SNR is less than -4 dB (that is, when SNR 4dB), the optimal RB allocation may result in a non-zero throughput, whereas for all the available RBs (that is, 66 RBs), the throughput may be zero ( = 0). In another example, when the SNR is greater than -4 dB, and less than or equal to 5 dB (that is, when -4dB < SNR 5dB), the throughput ( ) with optimal number of RBs and optimum MCS may be greater than the (that is, ).In another example, when the SNR is greater than 5 dB (that is, when SNR > 5dB), the throughput ( ) may be equivalent to the (that is, ). For a given SNR, maximum throughput may be achieved by transmitting only across the RBs with the highest JPTA beam gains, since throughput loss in case the transmission is performed across all the available RBs.

[0176] Figure 13illustrates a plot 1300 for percentage loss when all the 66 available RBs are used as a function of SNR, according to an embodiment of the present disclosure.

[0177] In an implementation, as referred to in Figure 13, the percentage loss may be computed using the [equation 9]:

[0178] [equation 9]

[0179]

[0180] [Table 3] given below depicts the results of a maximum loss percentage and an average loss percentage in throughput a Phased Antenna Array (PAA), a maximum loss percentage and an average loss percentage in throughput across component carriers (CC 1-4) associated with beam 1, and a maximum loss percentage and an average loss percentage in throughput across the CC 5-8 associated with beam 2 corresponding to different SNR regimes. The CC may be an individual frequency block that may be aggregated with other CC to form a wider transmission channel. Each CC may have bandwidth (e.g., 5, 10, 20 MHz). Furthermore, the CC may be configured independently in terms of frequency, modulation, and numerology.

[0181] ParametersSNR 4dB-4dB < SNR 5dBSNR > 5dBMax. loss in throughput PAA (%)10024.30911.1780Avg. loss in throughput PAA (%)89.22038.53270.0576Max. loss in throughput CC 1-4 (beam 1) (%)10038.82668.4483Avg. loss in throughput CC 1-4 (beam 1) (%)10016.16170.4960Max. loss in throughput CC 5-8 (beam 2) (%)10031.11469.6202Avg. loss in throughput CC 5-8 (beam 2) (%)10012.38490.3644

[0182] The results in [Table 3] and Figure 13 depict that the RB allocation may be critical in the JPTA, since an improper full-bandwidth allocation may cause a complete throughput loss (up to 100%) under a low SNR regime (SNR -4dB). Further, [Table 3] depicts a significant reduction of up to 38% in a low-medium SNR regime ( -4dB < SNR 5dB). Thus, a non-selective full-bandwidth allocation may lead to severe throughput degradation.

[0183] Figure 14illustrates a plot 1400 showing the difference between the SNR and the EESM as a function of SNR, according to an embodiment of the present disclosure.

[0184] As referred to in Figure 14c, the difference between the SNR and the EESM appeared around 0.6 dB at 9.1 dB SNR. The difference shows that EESM provides a better estimate of equivalent SNR in the presence of frequency selective JPTA beam gains. Thus, in an advantageous aspect, the disclosed system 210 and method 1000 provide the scheduling and link adaptation strategy that dynamically leverages each UE's SNR regime. The disclosed system 210 and method 1000 determine the optimal number of RBs to assign, select RB indices with favorable gain characteristics, and adjust the MCS value for each UE to maximize throughput. The examples explained for smart resource allocation, in scenarios where SNR is very low, poor RB assignment depicted the complete loss in throughput (up to 100%), and even under low-to-moderate SNR conditions, improper allocation depicted substantial throughput degradation, reaching up to 38%. Such results highlight the critical need for adaptive resource management in JPTA-enabled communication systems.

[0185] The present invention provides various advantages. For example, the present invention integrates the JPTA architectures into the beamforming technique, offering a compelling solution for enhancing transmission opportunities and overall UE throughput in next-generation wireless systems. By combining the plurality of analog phase shifters 110 with TTD elements, JPTA enables frequency-dependent beamforming, allowing multiple UEs to be served simultaneously across different frequency bands, even with a reduced number of RF chains. The spectral efficiency is improved, and the hardware complexity is also significantly lowered, as TTD components are simpler and more energy-efficient compared to the fully digital architectures that require extensive RF chain deployment. The present invention also leverages JPTA-equipped BS 204 to mitigate performance degradation typically observed at the band edges due to frequency-selective beam gains. To further optimize throughput, especially for cell-edge UEs operating in low-to-medium signal-to-noise ratio (SNR) conditions, the system 210 employs intelligent RB allocation strategies. The smart RB allocation techniques prioritize high-gain RBs and tailor MCS accordingly, resulting in substantial improvements in link reliability and data rates for UEs in challenging radio environments.

[0186] While specific language has been used to describe the disclosure, any limitations arising on account of the same are not intended. As would be apparent to a person in the art, various working modifications may be made to the method to implement the inventive concept as taught herein. The drawings and the foregoing description give examples of embodiments. Those skilled in the art will appreciate that one or more of the described elements may well be combined into a single functional element. Alternatively, certain elements may be split into multiple functional elements. Elements from one embodiment may be added to another embodiment. For example, orders of processes described herein may be changed and are not limited to the manner described herein.

Claims

1.A method performed by a base station for optimizing resource allocation in a Joint Phase Time Arrays (JPTA) wireless communication system, the method comprising:creating a sorted Resource Block (RB) list based on frequency-selective beam gains of a plurality of RBs, wherein the sorted RB list comprises the plurality of RBs in a descending order based on the corresponding frequency-selective beam gain;calculating a Signal-to-Noise Ratio (SNR) for each RB in the sorted RB list, based on a wideband SNR corresponding to a user equipment (UE) among a plurality of UEs and frequency-selective beam gain corresponding to the RB;computing a throughput value, for each of a combination of one or more calculated SNRs corresponding to the plurality of RBs and for associated Modulation and Coding Scheme (MCS) values corresponding to the plurality of RBs;determining an optimal MCS value and an optimal number of RBs for each of the plurality of UEs based on the computed throughput value and the wideband SNR for the corresponding UE;generating a mapping of the wideband SNR to the optimal number of RBs and the corresponding optimal MCS value; andallocating at least one of a number of RBs, corresponding RB indices, and corresponding MCS value to one or more UEs among the plurality of UEs using the mapping.2.The method of claim 1, further comprising:determining a number of beams to be used for the one or more UEs among the plurality of UEs;scheduling the one or more UEs based on the optimal number of RBs corresponding to the one or more UEs; andallocating the at least one of the number of RBs, the corresponding RB indices, and the corresponding MCS value for the corresponding scheduled one or more UEs using the mapping.3.The method of claim 2, wherein when a number of plurality of UEs is more than two for a beam among a plurality of beams in the JPTA wireless communication system, further comprising:allocating one or more RBs associated with a first frequency range, with beam gain values more than or equal to a predefined beam gain threshold, to one or more UEs among the plurality of UEs with corresponding SNR below a predefined threshold; andallocating one or more RBs associated with a second frequency range, with beam gain values less than the predefined beam gain threshold, to the one or more UEs among the plurality of UEs with corresponding SNR above the predefined threshold.4.The method of claim 1, wherein the mapping further comprises a plurality of RB indices corresponding to the optimal number of RBs.5.The method of claim 1, further comprising:computing the throughput value using one of an Exponential Effective SNR Mapping (EESM) technique, a Mean Mutual Information per Symbol (MMIS) technique, and a Received Bit Information Rate (RBIR) technique.6.The method of claim 1, wherein the JPTA wireless communication system operates using a 6thGeneration (6G) wireless communication network.7.The method of claim 1, further comprising:allocating the at least one of the number of RBs, the corresponding RB indices, and the corresponding MCS value to the one or more UEs for an uplink communication and a downlink communication.8.A base station for optimizing resource allocation in a Joint Phase Time Arrays (JPTA) wireless communication system, the base station comprising:at least one transceiver;at least one processor communicatively coupled to the at least one transceiver; andat least one memory, communicatively coupled to the at least one processor, storing instructions executable by the at least one processor individually or in any combination to cause the base station to:create a sorted Resource Block (RB) list based on frequency-selective beam gains of a plurality of RBs, wherein the sorted RB list comprises the plurality of RBs in a descending order based on the corresponding frequency-selective beam gain,calculate a Signal-to-Noise Ratio (SNR) for each RB in the sorted RB list, based on a wideband SNR corresponding to a user equipment (UE) among a plurality of UEs and frequency-selective beam gain corresponding to the RB,compute a throughput value, for each of a combination of one or more calculated SNRs corresponding to the plurality of RBs and for associated Modulation and Coding Scheme (MCS) values corresponding to the plurality of RBs,determine an optimal MCS value and an optimal number of RBs for each of the plurality of UEs based on the computed throughput value and the wideband SNR for the corresponding UE,generate a mapping of the wideband SNR to the optimal number of RBs and the corresponding optimal MCS value, andallocate at least one of a number of RBs, corresponding RB indices, and corresponding MCS value to one or more UEs among the plurality of UEs using the mapping.9.The base station of claim 8, wherein the instructions executable by the at least one processor individually or in any combination further cause the base station to:determine a number of beams to be used for the one or more UEs among the plurality of UEs,schedule the one or more UEs based on the optimal number of RBs corresponding to the one or more UEs, andallocate the at least one of the number of RBs, the corresponding RB indices, and the corresponding MCS value for the corresponding scheduled one or more UEs using the mapping.10.The base station of claim 9, wherein when a number of plurality of UEs is more than two for a beam among a plurality of beams in the JPTA wireless communication system, the instructions executable by the at least one processor individually or in any combination further cause the base station to:allocate one or more RBs associated with a first frequency range, with beam gain values more than or equal to a predefined beam gain threshold, to one or more UEs among the plurality of UEs with corresponding SNR below a predefined threshold, andallocate one or more RBs associated with a second frequency range, with beam gain values less than the predefined beam gain threshold, to the one or more UEs among the plurality of UEs with corresponding SNR above the predefined threshold.11.The base station of claim 8, wherein the mapping further comprises a plurality of RB indices corresponding to the optimal number of RBs.12.The base station of claim 8, wherein the instructions executable by the at least one processor individually or in any combination further cause the base station to compute the throughput value using one of an Exponential Effective SNR Mapping (EESM) technique, a Mean Mutual Information per Symbol (MMIS) technique, and a Received Bit Information Rate (RBIR) technique.13.The base station of claim 8, wherein the JPTA wireless communication system operates using a 6thGeneration (6G) wireless communication network.14.The base station of claim 8, wherein the instructions executable by the at least one processor individually or in any combination further cause the base station to allocate the at least one of the number of RBs, the corresponding RB indices, and the corresponding MCS value to the one or more UEs for an uplink communication and a downlink communication.

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