Power distribution for enhanced MIMO capacity

Abstract

The present invention provides a method and system for enhancing multiple-input multiple-output (MIMO) channel capacity by leveraging structured power distribution. The method involves identifying orthogonal sub-carriers across multiple antennas, determining the total degrees of freedom based on the number of sub-carriers and the MIMO channel rank, and identifying all possible combinations of power distribution across these degrees of freedom. The method further includes distributing available power units in combinations using a structured allocation strategy. By transmitting signals using this novel power allocation approach, the invention achieves a channel capacity that increases superiorly with the signal-to-noise ratio (SNR), surpassing the traditional logarithmic capacity growth in conventional MIMO systems. The system comprises multiple transmit and receive antennas, a processor, and a memory storing instructions to execute the method. This approach optimizes spectral efficiency, enhances energy efficiency, and improves data rates while maintaining compatibility with existing communication technologies such as OFDM and beamforming. Additionally, it provides a scalable and adaptive solution for various MIMO configurations, ensuring practical feasibility in real-world deployments.

Description

[0001] Power Distribution for Enhanced MIMO Capacity

[0002] Field of the Invention

[0003] The present invention relates to wireless communication systems, and more particularly to a method and system for enhancing multiple-input multiple-output (MIMO) channel capacity through a structured power allocation across sub-bands and antennas.

[0004] Background of the Invention

[0005] Multiple-input multiple-output (MIMO) technology has become a cornerstone in modem communication systems due to its ability to enhance channel capacity and improve spectral efficiency. MIMO systems utilize multiple antennas at both the transmitter and receiver to exploit multipath propagation, enabling the transmission of multiple data streams simultaneously over the same frequency band.

[0006] The theoretical foundations of MIMO systems are rooted in information theory, particularly in the work of Claude Shannon on channel capacity. Shannon's capacity formula for a single-input single-output (SISO) system relates the maximum achievable data rate to the signal-to-noise ratio (SNR) through a logarithmic function. This relationship has been extended to MIMO systems, where the capacity scales with the minimum number of transmit and receive antennas.

[0007] Traditional MIMO implementations aim to increase capacity by leveraging spatial multiplexing and diversity techniques. However, these approaches often require increased power consumption compared to SISOsystems, as each additional antenna and associated radio frequency (RF) chain contributes to the overall power budget. This power-capacity trade-off presents challenges in scenarios where energy efficiency is a primary concern, such as in battery-powered devices or in networks with limited power resources.

[0008] The concept of channel rank in MIMO systems refers to the number of independent spatial streams that can be supported by the channel. Higher rank channels generally offer greater capacity potential but fully exploiting this potential while maintaining power efficiency remains an area of ongoing research and development.

[0009] As networks continue to evolve and data demands grow, there is an increasing focus on techniques that can maximize spectral efficiency and capacity without proportionally increasing power consumption. This has led to exploration of various power allocation strategies, antenna selection methods, and signal processing techniques aimed at optimizing MIMO performance under different channel conditions and system constraints.

[0010] As the communication landscape continues to advance, there is ongoing interest in developing innovative approaches that can push the boundaries of MIMO capacity while addressing practical considerations such as power efficiency, hardware complexity, and implementation feasibility.Objective of the Invention

[0011] The principal objective of the present invention is to provide a method and system for enhancing multiple-input multiple-output (MIMO) channel capacity through a structured power allocation technique across sub-bands and antennas.

[0012] Another objective of the present invention is to address the powercapacity trade-off in MIMO systems by introducing a novel power allocation strategy that distributes available power units across multiple degrees of freedom in a structured manner, including both spatial and frequency domains.

[0013] Another objective of the present invention is to maximize spectral efficiency without proportionally increasing power consumption, ensuring higher data throughput while maintaining energy efficiency.

[0014] Another objective of the present invention is to provide a flexible framework that can dynamically adapt to various channel conditions and system constraints, enhancing the reliability and performance of communication systems.

[0015] Another objective of the present invention is to offer a scalable solution applicable to MIMO systems with different numbers of antennas and sub-carriers, ensuring compatibility across diverse communication standards and deployments.

[0016] Another objective of the present invention is to enable seamless integration with existing MIMO-based technologies, such as OFDM andbeamforming, to further improve system performance and enhance overall network efficiency.

[0017] Another objective of the present invention is to address challenges related to hardware complexity and implementation feasibility by introducing an efficient power distribution mechanism that minimizes the burden on practical MIMO system designs.

[0018] A further objective of the present invention is to improve energy efficiency in MIMO networks by strategically distributing power resources across spatial and frequency domains, reducing unnecessary power consumption while maintaining high data rates.

[0019] Summary of the Invention

[0020] This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter.

[0021] According to an aspect of the present invention, a method for enhancing multiple-input multiple-output (MIMO) channel capacity is provided. The method includes identifying a number of orthogonal subcarriers across multiple antennas in a MIMO system. The method further includes determining a total number of degrees of freedom based on the number of orthogonal sub-carriers and the rank of the MIMO channel. The method also includes distributing available power units across the totalnumber of degrees of freedom using a structured power allocation technique. Additionally, the method includes transmitting signals using the distributed power units to achieve a channel capacity that increases superiorly with signal-to-noise ratio (SNR).

[0022] According to other aspects of the present invention, the method may include one or more of the following features. The number of orthogonal sub-carriers may be determined based on available bandwidth and a desired sub-carrier spacing. The rank of the MIMO channel may be determined based on the number of independent spatial streams supported by the channel. Distributing the available power units may comprise identifying all possible combinations of power distribution across the total number of degrees of freedom and selecting a combination that maximizes channel capacity. Each combination may represent a signal transmitted by all transmitter antennas and received by all receiver antennas. The method may further comprise coupling each transmit-receive antenna pair with a radio frequency (RF) chain to receive data symbols. Each transmit-receive antenna pair may have an equal number of sub-bands, and the total bandwidth may be divided equally among the sub-bands.

[0023] According to another aspect of the present invention, a system for enhancing multiple-input multiple-output (MIMO) channel capacity is provided. The system includes multiple transmit antennas, multiple receive antennas, a processor, and a memory storing instructions. When executed by the processor, the instructions cause the system to identify a number oforthogonal sub-carriers across the multiple transmit and receive antennas, determine a total number of degrees of freedom based on the number of orthogonal sub-carriers and the rank of the MIMO channel, distribute available power units across the total number of degrees of freedom using a structured allocation strategy, and transmit signals using the distributed power units to achieve a channel capacity that increases superiorly with signal-to-noise ratio (SNR).

[0024] According to other aspects of the present invention, the system may include one or more of the following features. The instructions may further cause the system to determine the number of orthogonal sub-carriers based on available bandwidth and a desired sub-carrier spacing. The instructions may further cause the system to determine the rank of the MIMO channel based on the number of independent spatial streams supported by the channel. Distributing the available power units may comprise identifying all possible optimized power allocation patterns across the total number of degrees of freedom and selecting an allocation that maximizes channel capacity. Each allocation may represent a signal transmitted by all transmitter antennas and received by all receiver antennas. The system may further comprise multiple radio frequency (RF) chains, wherein each transmit-receive antenna pair is coupled with an RF chain to receive data symbols. Each transmit-receive antenna pair may have an equal number of sub-bands, and the total bandwidth may be divided equally among the subbands.According to yet another aspect of the present invention, a non-transitory computer-readable medium storing instructions is provided. When executed by a processor, the instructions cause the processor to perform a method for enhancing multiple-input multiple-output (MIMO) channel capacity. The method includes identifying a number of orthogonal subcarriers across multiple antennas in a MIMO system, determining a total number of degrees of freedom based on the number of orthogonal subcarriers and the rank of the MIMO channel, distributing available power units across the total number of degrees of freedom using a structured power allocation approach, and transmitting signals using the distributed power units to achieve a channel capacity that increases superiorly with signal-to-noise ratio (SNR).

[0025] According to other aspects of the present invention, the method performed by the non-transitory computer-readable medium may include one or more of the following features. The method may further comprise determining the number of orthogonal sub-carriers based on available bandwidth and a desired sub-carrier spacing. The method may further comprise determining the rank of the MIMO channel based on the number of independent spatial streams supported by the channel. Distributing the available power units may comprise identifying all possible structured combinations of power distribution across the total number of degrees of freedom and selecting a combination that maximizes channel capacity. Each combination may represent a signal transmitted by all transmitterantennas and received by all receiver antennas. The method may further comprise coupling each transmit-receive antenna pair with a radio frequency (RF) chain to receive data symbols, wherein each transmitreceive antenna pair has an equal number of sub-bands, and a total bandwidth is divided equally among the sub-bands.

[0026] Brief description of the drawings

[0027] The figures described below depict various aspects of the system and methods disclosed herein. It should be understood that each figure depicts an embodiment of a particular aspect of the disclosed system and methods, and that each of the figures is intended to accord with a possible embodiment thereof. Further, wherever possible, the following description refers to the reference numerals included in the following figures, in which features depicted in multiple figures are designated with consistent reference numerals.

[0028] FIG. 1 illustrates Comparison of Shannon Capacity and Structured Power Allocation Capacity (100) as a Function of Signal-to-Noise Ratio (SNR) for Sub-Band Widths of 15 kHz in a MIMO System, according to one embodiment of the present invention.

[0029] FIG.2 illustrates a block diagram of a Structured Power Allocation and Rank-Adaptive MIMO Transmission System (200), in accordance with one embodiment of the present invention.FIG.3 depicts a flowchart outlining the process of power distribution across sub-bands in a MIMO system (300), in accordance with one embodiment of the present invention.

[0030] Persons skilled in the art will appreciate that elements in the figures are illustrated for simplicity and clarity and may have not been drawn to scale. For example, the dimensions of some of the elements in the figure may be exaggerated relative to other elements to help to improve understanding of various exemplary embodiments of the present disclosure.

[0031] Throughout the drawings, it should be noted that like reference numbers are used to depict the same or similar elements, features, and structures.

[0032] Detailed Description of the Invention

[0033] The following description with reference to the accompanying drawings is provided to assist in a comprehensive understanding of exemplary embodiments of the invention as defined by the claims and their equivalents. It includes various specific details to assist in that understanding but these are to be regarded as merely exemplary.

[0034] Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the invention. In addition, descriptions of well-known functions and constructions are omitted for clarity and conciseness.The terms and words used in the following description and claims are not limited to the bibliographical meanings but are merely used by the inventor to enable a clear and consistent understanding of the invention. Accordingly, it should be apparent to those skilled in the art that the following description of exemplary embodiments of the present invention are provided for illustration purpose only and not for the purpose of limiting the invention as defined by the appended claims and their equivalents.

[0035] It is to be understood that the singular forms “a,” “an,” and “the” include plural referents unless the context clearly dictates otherwise. Thus, for example, reference to “a component surface” includes reference to one or more of such surfaces.

[0036] By the term “substantially” it is meant that the recited characteristic, parameter, or value need not be achieved exactly, but that deviations or variations, including for example, tolerances, measurement error, measurement accuracy limitations and other factors known to those of skill in the art, may occur in amounts that do not preclude the effect the characteristic is intended to provide.

[0037] Figures discussed below, and the various embodiments used to describe the principles of the present disclosure in this patent document are by way of illustration only and should not be construed in any way that would limit the scope of the disclosure. Those skilled in the art will understand that the principles of the present disclosure may be implemented in any suitably arranged system. The terms used to describe various embodiments areexemplary. It should be understood that these are provided to merely aid the understanding of the description, and that their use and definitions, in no way limit the scope of the invention. Terms first, second, and the like are used to differentiate between objects having the same terminology and are in no way intended to represent a chronological order, unless where explicitly stated otherwise. A set is defined as a non-empty set including at least one element.

[0038] The present invention provides methods and systems for optimizing channel capacity in multiple-input multiple-output (MIMO) communication systems. Specifically, the invention describes a technique for distributing transmission power across multiple degrees of freedom within a MIMO system to achieve enhanced spectral efficiency and capacity. By strategically allocating power across spatial and frequency-domain resources, the disclosed approach improves system performance while maintaining energy efficiency.

[0039] MIMO technology utilizes multiple transmit and receive antennas to establish independent signal paths, thereby increasing data throughput and link reliability. Traditional MIMO implementations often rely on powerintensive transmission schemes to maximize capacity, leading to inefficient power utilization. The present invention introduces a novel power distribution technique that systematically allocates available power to optimize MIMO channel capacity without incurring excessive energy consumption.The disclosed technique employs a structured power allocation approach that leverages the spatial independence or rank of the MIMO channel, along with the available sub-bands. By distributing power across these dimensions in an optimized manner, the method ensures efficient utilization of system resources. This enables a more scalable and adaptive communication strategy, particularly in scenarios where power efficiency is a critical factor.

[0040] By implementing the structured power distribution mechanism, the MIMO system achieves an improved channel capacity that grows more favourably with signal-to-noise ratio (SNR) compared to conventional methods. This innovative approach not only enhances the overall performance of MIMO systems but also facilitates energy-efficient transmission, making it particularly beneficial for power-sensitive applications and next-generation communication networks.

[0041] Figure 1 illustrates a comparison between Shannon capacity and Structured Power Allocation capacity (100), highlighting the differences in capacity scaling under one embodiment of the present invention. The disclosed capacity comparison demonstrates the advantages of Structured Power Allocation over conventional Shannon-based techniques by enabling superior capacity growth with power, thereby overcoming the inherent logarithmic constraints of Shannon’s model.

[0042] In some cases, presents an capacity comparison graph (100), showing the relationship between Shannon capacity and Structured PowerAllocation capacity for different values of N and K. The x-axis represents K values ranging from 1 to 16, while the y-axis plots capacity in bits per second (bps). The graph includes multiple curves comparing Shannon and Structured Power Allocation capacity under different configurations, specifically:

[0043] • Shannon capacity for N = 8, K = 16

[0044] • Structured Power Allocation capacity for N = 8, K = 8, Rank = 2

[0045] The graphical representation demonstrates that Shannon capacity follows a logarithmic function of SNR, leading to diminishing returns as SNR increases. In contrast, the disclosed Structured Power Allocation capacity model exhibits a superior growth pattern, wherein an increase in K results in a superior logarithmic increase in capacity.

[0046] The capacity comparison graph may further indicate a bandwidth value Bs= 15KHz. Such information may be utilized by the bandwidth splitting module to determine optimal sub-band divisions and by the power allocator to make power distribution decisions that leverage the superior capacity enhancement provided by the Structured Power Allocation model.

[0047] In one embodiment, Shannon’s theorem has traditionally been interpreted in terms of time-domain pulse modulation, restricting capacity computations to a singular bandwidth B without considering combination effects in frequency domain distribution. The present invention introduces an alternative interpretation of Shannon’s theorem in the frequency domainby partitioning the given bandwidth B into N sub-bands or N sub-carriers, thereby enabling the discovery of increased capacity.

[0048] While conventional techniques such as Orthogonal Frequency Division Multiplexing (OFDM) employ N sub-bands, they primarily focus on distributing the available power equally across the sub-bands. In contrast, in one embodiment, the present invention utilizes a Structured Power Allocation Capacity scheme that maximizes the number of waveform combinations rather than merely optimizing power distribution based on convex log function properties. The method of distributing available power over the sub-bands using Structured Power Allocation results in offering a significant improvement over traditional technique.

[0049] To mathematically illustrate this approach, the total bandwidth B is divided into N sub-bands, each having bandwidth BS=B / N. Similarly, the total available power P, which was previously distributed across the entire bandwidth B, be partitioned into K power segments, where each segment receives a power proportional to or at least equal to the product of the noise

[0050]

[0051] power spectral density Noand the sub-band bandwidth Bs;that is, K = c BsNo where c is the proportionality constant. . By redefining the Shannon capacity formula under this framework, we obtain:

[0052]

[0053] <

[0054] where:

[0055] • C represents the channel capacity,

[0056] • B denotes the total channel bandwidth,• P is the signal power across the entire bandwidth B,

[0057] • o2is the noise power across the entire bandwidth B.

[0058] By extending this interpretation to the Structured Power Allocation framework, where N subcarriers of Bsbandwidth are utilized, the capacity equation transforms into:

[0059]

[0060] <

[0061] Here we are dividing the bandwidth into N sub-bands, that is, B = N * Bs. So the terms inside the log() function should be now interpreted per subband; meaning as given below:

[0062] • P is the signal power across the sub-band,

[0063] • o2is the noise power across the sub-band.

[0064]

[0065] For the case when = 1, for a 2-PAM or BPSK modulated system, the

[0066]

[0067] above equation simplifies to:

[0068]

[0069] Here, the term inside the logarithm, (1+1)N, follows the binomial expansion principle, revealing a novel interpretation based on Structured Power Allocation. Unlike conventional utility maximization techniques, such as the water-pouring algorithm which distributes power across available sub-bands to maximize the sum capacity the present invention introduces a paradigm shift by addressing power distribution as a Structured Power Allocation problem.

[0070] In this approach, the Structured Power Allocation framework enhances channel throughput by identifying and applying various combinations ofpower levels across the sub-bands, thereby optimizing spectral efficiency and improving overall system performance.

[0071] In one embodiment, the problem of distributing K power units across N sub-bands is equivalent to distributing K identical units across N distinct bins, which leads to a new channel capacity formula:

[0072] >

[0073]

[0074] where:

[0075] • N > 1 represents the number of orthogonal sub-carriers,

[0076] • K denotes the number of power units (in terms of noise power per sub-band oA2), and in a way K is a normalized power, though it has appearance of SNR.

[0077]

[0078] • = Bsrepresents the bandwidth per sub-carrier,

[0079]

[0080] • C accounts for a single quadrature component (either I- or Q- component).

[0081] To account for both quadrature components (I and Q), N must be replaced with 2N, leading to a revised capacity expression. This is another way of saying that the sub-band has one or two quadrature components, over which the power can be distributed. A test case verification done for BPSK system, where N = 1 and K = 1, results in M=3 as per the above formula. However, in order to have same distance between the levels and the same average power of K=1 , as available in BPSK, a skilled person willnot set i=0 in the above summing formula for M. This will give us M=2 when i=1:

[0082]

[0083] Note this selection of appropriate value of M (that is, instead of using M=3 we are using M=2) is part of another patent application - optimal PAM. We give few examples on computing M:

[0084] • N=1, K=1 CQ CQ 2° + C^C^1= 1 + 2 = 3 combinations

[0085]

[0086] 3 x 3 x 4 + 1 x 1 x 8 = 1 + 18 + 36 + 8 = 63 combinations.

[0087] In structured power allocation MIMO, N represents the total degrees of freedom (number of subcarriers multiplied by channel rank). Therefore,

[0088] N = Number of subcarriers * Rank

[0089] The number of power units K is given by:

[0090]

[0091] Here P is power per transmit-receive pair. In some cases, by employing structured power allocation, the present invention overcomes the limitations of conventional Shannon-based capacity models, enabling superior growth in channel capacity with respect to SNR. Unlike traditional power allocation methods, which distribute power uniformly or based on a water-filling approach, the structured power allocation technique evaluatesall feasible combinations of power allocation and selects the optimal configuration to maximize capacity while minimizing power consumption. This structured approach ensures that the available power is systematically distributed across sub-bands and antennas, resulting in improved energy efficiency. By effectively utilizing structured power allocation, the invention provides enhanced performance, making it particularly beneficial for nextgeneration communication systems requiring high data rates with constrained power budgets.

[0092] Figure 1 shows that Shannon-MIMO capacity (line with bars or vertical lines) is two times the Shannon-SISO capacity (line with circles) for Rank = 2; for this Shannon-MIMO uses double the power. However, the instant invention for MIMO (line with upward triangles) shows more capacity at the same power as Shannon-SISO. Instant invention for MIMO ‘does not’ use two times the power. The instant invention for MIMO shows superior capacity because it exploits the available extra degrees of freedom = NxRank = 16 degrees for the same power sweep upto KxRank = Kx2 = 2K = 2x8 = 16 units.

[0093] Figure 2 illustrates a block diagram of a Structured Power Allocation and Rank-Adaptive MIMO Transmission System (200), in accordance with an embodiment of the present invention. The system facilitates the transmission and reception of signals over a multiple-input multiple-output (MIMO) communication channel while optimizing channel capacity through a structured power allocation technique.The system comprises an Input, a Sub-Carrier Identification Module (205), a MIMO Channel Rank Estimation Module (210), a Power Distribution Module (215), a MIMO Transmitter Module (220), a Channel Compensation Module (225), a MIMO Receiver Module (230), and an Output Processing Module (235), all of which are communicatively coupled to execute the structured power allocation technique for efficient signal transmission.

[0094] In one embodiment, the Sub-Carrier Identification Module (205) is configured to receive the input bits and identify available orthogonal subcarriers within a predefined system bandwidth. The module partitions the available bandwidth into discrete sub-bands, each representing an independent frequency component for data transmission. The identified sub-carriers are allocated to different MIMO transmission paths, thereby leveraging frequency diversity and improving spectral efficiency.

[0095] The MIMO Channel Rank Estimation Module (210) determines the rank of the MIMO channel based on channel state information (CSI). The module computes the singular value decomposition (SVD) of the channel matrix to estimate the number of independent spatial data streams that can be transmitted simultaneously. The estimated rank is a key parameter in the structured power allocation technique, as it dictates the number of degrees of freedom available for power allocation.

[0096] The Power Distribution Module (215) implements a structured power allocation technique, which involves:• Identifying all possible combinations of power distribution across the total number of degrees of freedom. Each combination represents a distinct way of allocating power across sub-carriers and spatial streams, ensuring optimal resource utilization.

[0097] • Evaluating the channel capacity for each identified combination to determine an optimal power allocation strategy that maximizes spectral efficiency while minimizing power consumption.

[0098] • Utilizing the optimal combination by assigning power levels to the identified sub-carriers and MIMO spatial streams.

[0099] The power distribution module adapts the power allocation dynamically based on variations in channel conditions and signal-to-noise ratio (SNR). The optimized power distribution strategy is then forwarded to the MIMO Transmitter Module (220) for implementation.

[0100] The MIMO Transmitter Module (220) transmits the structured power-allocated signals over multiple antennas. The transmitter module employs pre-processing for beamforming, spatial multiplexing, or diversity schemes based on the estimated channel rank and allocated power levels. The transmitted signals propagate through the channel, where they are subject to noise, fading, and interference.

[0101] The Channel Compensation Module (225) processes the received signals to mitigate channel impairments. The compensation module applies equalization techniques, interference cancellation algorithms, and adaptive filtering to enhance signal quality and restore transmitted data integrity.The MIMO Receiver Module (230) receives the transmitted signals through multiple antennas and applies detection and decoding mechanisms. The receiver module employs post-processing for spatial filtering and multi-stream separation techniques to recover the transmitted information with minimal error. The extracted data streams are then forwarded for further processing.

[0102] The Output Processing Module (235) processes the decoded data for subsequent transmission, storage, or application. The processed output may include reconstructed data packets, error-corrected information, or other forms of communication data ready for delivery to the intended recipient.

[0103] Figure 3 illustrates a flowchart depicting a method for structured power allocation in a Multiple-Input Multiple-Output (MIMO) system (300). The method enables the systematic distribution of transmission power across multiple degrees of freedom, including sub-bands and spatial transmission paths, to optimize spectral efficiency and channel capacity. The structured power allocation technique ensures that power is distributed in all possible ways across the available transmission resources, thereby achieving an efficient utilization of available power.

[0104] The method begins with receiving an input bits, wherein the system acquires data for transmission over a MIMO communication channel. The system proceeds to identify the number of orthogonal sub-carriers across multiple antennas (305). This identification process involves analyzing theavailable bandwidth and partitioning it into discrete sub-carriers, ensuring that each sub-carrier remains orthogonal to others to minimize inter-carrier interference. The identified sub-carriers form independent transmission paths that enhance frequency diversity in the MIMO system.

[0105] The system then determines the total number of degrees of freedom (310) by evaluating the available sub-carriers in conjunction with the estimated MIMO channel rank. The rank of the MIMO channel is determined based on the number of independent spatial transmission paths available for data transmission. The degrees of freedom are represented as the product of the number of orthogonal sub-carriers and the rank of the channel. This step establishes the transmission resources available for structured power allocation.

[0106] Once the total degrees of freedom are determined, the system proceeds to distribute available power units across the identified degrees of freedom in all possible ways (315). The power allocation process involves evaluating multiple combinations of power distribution across the available sub-carriers and spatial streams. The power units, defined in terms of noise power, are systematically assigned to transmission paths using a structured power allocation technique, ensuring that the system explores all potential power distribution strategies to maximize capacity. The structured power allocation technique dynamically selects the optimal combination that maximizes capacity while maintaining energy efficiency.Following power allocation, the system transmits signals using the distributed power units (320). The transmission module modulates the data onto the selected sub-carriers and spatial transmission paths, ensuring that power is effectively utilized to enhance the system's Signal-to-Noise Ratio (SNR). The structured power allocation approach enables the MIMO system to achieve a superior increase in capacity as a function of SNR, surpassing the conventional logarithmic capacity growth observed in traditional MIMO systems.

[0107] The system then dynamically adjusts power allocation (325) to compensate for real-time channel impairments such as path loss, fading, and noise variations. This adaptive power allocation ensures that transmission power is continuously optimized to account for varying channel conditions, further improving system reliability and spectral efficiency.

[0108] The structured power allocation method enables higher data transmission rates while reducing power consumption. By systematically evaluating and distributing power in all possible ways across sub-bands and spatial dimensions, the system achieves superior capacity gains compared to conventional MIMO systems, making it particularly advantageous for high-efficiency communication networks.

[0109] A number of implementations have been described. Nevertheless, it will be understood that various modifications may be made without departing from the spirit and scope of the disclosure. Accordingly, other implementations are within the scope of the following claims.

Claims

We Claim:

1. A method for enhancing multiple-input multiple-output (MIMO) channel capacity, comprising:identifying a number of orthogonal sub-carriers across multiple antennas in a MIMO system (305);determining a total number of degrees of freedom based on the number of orthogonal sub-carriers and a rank of the MIMO channel (310);distributing available power units across the total number of degrees of freedom using a structured power allocation technique (315), wherein the power units are defined in terms of noise power; andtransmitting signals using the distributed power units to achieve a channel capacity that increases with signal-to-noise ratio (SNR) (320).

2. The method as claimed in claim 1, wherein the structured power allocation technique comprises:identifying all possible combinations of power distribution across the total number of degrees of freedom; andutilizing all identified combinations to enhance channel capacity.

3. The method as claimed in claim 1 , wherein the number of orthogonal sub-carriers is determined based on available bandwidth and a desired subcarrier spacing, wherein sub-carrier includes one or both quadrature components, cosine or sine components.

4. The method as claimed in claim 1, wherein the rank of the MIMO channel is determined based on the number of independent spatial streams supported by the channel.

5. The method as claimed in claim 2, wherein each combination represents a signal transmitted by all transmitter antennas and received by all receiver antennas.

6. The method as claimed in claim 1 , further comprising:coupling each transmit-receive antenna pair with a radio frequency (RF) chain to receive data symbols.

7. The method as claimed in claim 6, wherein each transmit-receive antenna pair has an equal number of sub-bands, and the total bandwidth is divided equally among the sub-bands.

8. The method as claimed in claim 1, wherein the noise power is estimated dynamically to optimize power distribution and improve overall channel capacity.

9. The method as claimed in claim 1 , further comprising compensating for channel impairments including path loss, noise, and fading by dynamically adjusting power allocation across the degrees of freedom.

10. A system for enhancing multiple-input multiple-output (MIMO) channel capacity, comprising:multiple transmit antennas;multiple receive antennas;a processor; anda memory storing instructions that, when executed by the processor, cause the system to:identify a number of orthogonal sub-carriers across the multiple transmit and receive antennas;determine a total number of degrees of freedom based on the number of orthogonal sub-carriers and a rank of the MIMO channel;distribute available power units across the total number of degrees of freedom using a structured power allocation technique, wherein the power units are defined in terms of noise power; andtransmit signals using the distributed power units to achieve a channel capacity that increases with signal-to-noise ratio (SNR).

11. The system as claimed in claim 10, wherein the instructions further cause the system to determine the number of orthogonal sub-carriers based on available bandwidth and a desired sub-carrier spacing.

12. The system as claimed in claim 10, wherein the instructions further cause the system to determine the rank of the MIMO channel based on the number of independent spatial streams supported by the channel.

13. The system as claimed in claim 10, wherein the structured power allocation technique comprises:identifying all possible combinations of power distribution across the total number of degrees of freedom; andutilizing all identified combinations to enhance channel capacity.

14. The system as claimed in claim 13, wherein each combination represents a signal transmitted by all transmitter antennas and received by all receiver antennas.

15. The system as claimed in claim 10, further comprising multiple radio frequency (RF) chains, wherein each transmit-receive antenna pair is coupled with an RF chain to receive data symbols.

16. The system as claimed in claim 15, wherein each transmit-receive antenna pair has an equal number of sub-bands, and the total bandwidth is divided equally among the sub-bands.

17. The system as claimed in claim 10, wherein the instructions further cause the system to compensate for channel impairments including path loss, noise, and fading by dynamically adjusting power allocation across the degrees of freedom.

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