Method for adaptive uplink link adaptation in ntn

Abstract

Method for Adaptive Uplink Link Adaptation in NTN The present invention relates to a method for adaptive uplink link adaptation in communication applications, especially where latency and power consumption are critical. The invention also focuses on link adaptation resilient to channel changes.

Description

[0001] Method for Adaptive Uplink Link Adaptation in NTN

[0002] TECHNICAL FIELD

[0003] The present invention relates to a method for Adaptive Uplink Link Adaptation in NTN.

[0004] PRIOR ART

[0005] Today, improving the robustness and reliability of wireless transmissions, are important issues in communication systems. One of the techniques used for robustness and reliability of wireless transmissions is link adaptation. Link adaptation (LA) can significantly increase the spectral efficiency and render various levels of services, both of which are highly desirable for today's high-speed communication systems.

[0006] Conventional link adaptation techniques in wireless networks aim to overcome harsh link conditions caused by physical environmental properties, by adaptively regulating modulation, coding and other signal and protocol specific parameters. These techniques are essential for the overall performance of the networks, especially for environments where the ambient noise level is high or the noise level changes rapidly.

[0007] When examining link adaptation in more detail, link adaptation, having 3 types as uplink I downlink I sidelink, is a so critical phenomenon to adjust both power of the transmitted signal and modulation level for communication systems. Uplink link adaptation process relies on feedback mechanisms obtained by wireless node. It depends on which channel is used, PRACH (Physical Random Access Channel), PUSCH (Physical Uplink Shared Channel), PUCCH (Physical Uplink Control Channel), SRS (Sounding Reference Signal).

[0008] The main problems for NTN link adaptation mechanism is propagation delay. When taking into consideration closed loop control mechanism, this problem decreases communication performance. This case is underlined in TS 38.81 1 section 7. To cope with this issue, for instance User Equipment (UE)’s set their power levels almost 2 dB higher than they should be. This means battery problem for UE.

[0009] In order to improve the performance of link adaptation, patent documents in the state of the art are reviewed below. Also, the papers written for the purpose of sensing assisted communication are summarized as well.

[0010] In given reference document

[0001] , V2X sidelink link adaptation is achieved by obtaining both location information from sensors on vehicles and feedback from the second apparatus. It examines the correlation of parameters such as PMI (precoding matrix indicator), Rl (Rank Indicator), and CQI (Channel Quality Indicator) to determine Line- of-Sight (LOS) conditions. If LOS is present, it adjusts transmission parameters such as data rate and DMRS (Demodulation Reference Signal) density, code rate, precoder, CSI-RS (Channel State Information Reference Signal), feedback rate, beamwidth for second transmission. Otherwise, it will not change any transmission parameter for second transmission. This patent document pertains to the link that has been established with the aim of enhancing its more efficient utilization. However, if the link is disrupted, these steps will be reinitiated.

[0011] In given reference document [2], it is aimed at downlink link adaptation for OFDMA network by analysing channel feedback obtained from each of UE’s connected to base station (BS). In this patent, channel gains from all the user equipment’s (UE’s) are obtained for each OFDM subcarrier. Then BS reorder Resource Blocks (RB’s) and assign data bits to each of subcarriers with respect to channel gains to achieve optimum throughput. The patent document is related to downlink link adaptation and not suggested any extra method to avoid link disconnections. And it just exploits channel feedback without utilizing any sensing method .

[0012] In given reference document [3], downlink link adaptation for interference cancelling (IC) receivers by analysing UE interference efficiency reports is aimed. In this application, it is assumed that the communication network is an HetNet, and the target users are those located at the cell edge and experiencing severe interference. To adjust link adaptation for these users, BS obtains which transport format is used from the network. Then it sends the same content to the interference cancelling UE to measure the cancellation efficiency of UE and channel quality, CSI / CQI / SINR. Finally, BS adapts transport format by considering interference capability. The patent document is related to downlink link adaptation in the interference prone environments, HetNet. And it is not recommended any method to enhance link adaptation for faded environments.

[0013] In given reference document [4], fast uplink power control is aimed by being obtained transmit power control commands and transmit control mapping tables created with respect to RSRP, RSRQ, RSSI measurements from BS. These tables are created per each channel, PUCCH / PUSCH / SRS. This patent document is based on information exchange between the BS (Base Station) and UE (User Equipment). It includes signalling, but a dynamic mechanism has not been proposed. After the link is severed, the same procedures will be repeated.

[0014] In given reference document [5], the aim of this patent is enabling downlink link adaptation for low-cost UE’s. BS sends control data to the UE’s via PDCCH (physical downlink control channel) and obtains CQI measurements from all the UE’s. Then BS adapts and configures PDSCH (physical downlink shared channel) frames to the UE’S. The aim of this patent document is to create frame design for PDSCH.

[0015] However, it should be noted that there are studies in the literature related to link adaptation techniques. Additionally, research can be found under the headings of handover studies and beamforming studies within the context of sensing-assisted communication.

[0016] In given reference document [6] and given reference document [7], algorithmic studies that adjust MCS (Modulation and Coding Scheme) levels based on CSI, RSRP, SINR, RSSI information obtained from the UE are conducted. But these studies do not intend a resilient link towards fast fading.

[0017] In given reference document [8], using RSRP (Reference Signal Received Power) and localization information obtained from UE’s, performs beam management towards the direction where the received signal is maximized with the Reinforcement Learning algorithm.

[0018] In given reference document [9], beam alignment for V2X communication in mmWave study is realized. In this study an external radar device is utilized to extract fingerprint map to direct beam. In the given reference document

[0010] beamforming study based radar sensing is executed as well. In this study, beam tracking technique is proposed by applying Extended Kalman Filter (EKF) technique.

[0019] At literature fingerprint-based studies are generally focused on localization, beam alignment via measurements like RSS (reference signal strength) based. In these works, some methods like learning based or statistical are suggested to interpret the outcomes given reference documents

[0011] and given reference document

[0012] ,

[0020] In given reference document

[0013] , path loss exponent and shadowing factor from channel parameters to predict are aimed from satellite images. The aim of this document is getting optimal network planning. To achieve this goal, an external camera has been utilized. Also, in the given reference document

[0014] , several computer visions aided communication techniques are introduced. RF channel prediction, multimodal prediction, and proactive decision-making aims can be sorted as the aims. But while doing that, external camera images are exploited.

[0021] Also, in the given reference document

[0015] spectrum sensing based handoff studies are shown. Channel sensing sequence-based spectrum handoff scheme, energy efficient spectrum sensing based spectrum handoff scheme, reactive and proactive sensing spectrum handoff scheme are demonstrated among the recommended spectrum sensing techniques. This purpose is different than the link adaptation issue. But this topic is being considered under the heading of Sensing Assisted Communication.

[0022] In the literature, the common property of the patents related to link adaptation is them to use feedback parameters like CQI, RSRP, RSRQ. Sensing based mechanism is not mentioned in documents. When examining patents and papers related to link adaptation, it is observed that there are no studies focusing on link adaptation resilient to channel changes. Existing literature primarily concerns the establishment of efficient links. There is no emphasis on enhancing link resilience against link disconnections. After the link is disconnected, it is aimed to re-establish the link using the method initially described. Furthermore, there is no coverage of link adaptation techniques addressing non terrestrial network (NTN) links. Additionally, the subject of dynamic link adaptation has not been addressed.

[0023] Link adaptation is a critical phenomenon for communication systems. There are three different links for link adaptation. These are;

[0024] 1 ) downlink link adaptation

[0025] 2) uplink link adaptation

[0026] 3) sidelink link adaptation

[0027] Parameters of link adaptation include adjusting the modulation level (Modulation Coding Scheme - MCS, adaptive coding modulation - ACM) and adjusting power control levels.

[0028] For uplink link adaptation, there are three different channels that involve bidirectional signaling between network node and wireless node.

[0029] 1 ) PUCCH (Physical Uplink Control Channel)

[0030] 2) PUSCH (Physical Uplink Shared Channel)

[0031] 3) SRS (Sounding Reference Signal) Channel

[0032] For each modulation level on these channels, different power levels need to be achieved at the receiver to provide link adaptation.

[0033] To reach the required power level and adapt MCS (Modulation and Coding Scheme) level for each selected channel, there is a feedback mechanism between the network node and the wireless node. Network node adjusts the link adaptation including MCS and power level for all the uplink and downlink channels by investigating CSI reports gathered by network node and obtained by network node or wireless node, SINR measurements and power measurements like RSRP, RSRQ, RSSI node . Scheduling for uplink link adaptation is made by network node then feedback is sent to wireless node. Based on this feedback, the wireless node can either increase its transmit power or change the modulation level under the control of the network node.

[0034] When considering this mechanism for NTN (non-terrestrial networks), LEO (Low Earth Orbit) satellites are located between 700 and 3000 kilometers above the Earth, while GEO (Geostationary orbit) satellites are at an altitude of 35,000 kilometers. In the context of traditional link adaptation procedures, this results in approximately a 500- millisecond Round Trip Time (RTT) delay for LEO. Linder these conditions, the times required for link adaptation would be approximately 750 milliseconds and 30 milliseconds respectively.

[0035] As mentioned, such a closed-loop scheme introduces propagation delay and leads to a degradation in communication performance. Consequently, it will result in a higher probability of error and error metrics like Bit Error Rate (BER) Block Error Rate (BLER) so the performance of the system will decrease.

[0036] This issue is explicitly addressed in the 3GPP specification document TS 38.81 1 titled "Study on New Radio (NR) to support non-terrestrial networks." The proposed solution is to set the output power of wireless nodes approximately 2 dB higher. However, this approach can lead to significant battery problems and energy issues for users.

[0037] This is a serious problem for NTN communication. Additionally, when considering NTN access points with very wide coverage areas, it is evident that the channel characteristics within the coverage area will vary significantly. In this scenario, wireless nodes will need to adapt their links when entering environments with different channel characteristics. Especially for fast-moving wireless nodes (e.g., vehicles, high-speed trains), rapid link adaptation is essential due to the fast-fading effect of the channel. If it does not happen, the link can be lost, leading to significant data loss. Re-establishing the link can result in the approximately 750 milliseconds of delay mentioned earlier. As a result, the channel change rate, being faster than the feedback rate, will lead to data loss.

[0038] The reasons for these challenges in NTN communication can be summarized as follows.

[0039] • Latency,

[0040] • Extra power consumption,

[0041] • Large scale fading and small scale fading characteristics of the communication channel making link adaptation critical for uplink communication in NTN networks.

[0042] All the problems mentioned above have made it necessary to make an innovation in the relevant technical field as a result.

[0043] BRIEF DESCRIPTION OF THE INVENTION

[0044] A key function in wireless networks is link adaptation. Link adaptation is aimed at estimating, based on available channel information, the most appropriate modulation order and coding rate to be used at a given time on a radio link to meet a target criterion.

[0045] The present invention relates to a method for adaptive uplink link adaptation in NTN to eliminate the above-mentioned disadvantages and bring new advantages to the relevant technical field.

[0046] The invention that the method for adaptive uplink link adaptation in communication applications, especially where latency and power consumption are critical. The invention also focuses on link adaptation resilient to channel changes.

[0047] An object of the invention is to develop a method for link adaptation in a non-terrestrial network (NTN). Non terrestrial network (NTN) plays a significant role for several reasons. GEO (Geostationary orbit) / LEO (Low Earth Orbit) I MEO (Medium Earth orbit) satellites, HAPS (High Altitude Platform Stations), drones can be utilized on behalf of NTN communication networks that extend beyond traditional terrestrial infrastructures. The advantages of NTN are listed some below.

[0048] 1 ) Wide coverage areas,

[0049] 2) Resilience to natural disasters, network congestion rather than terrestrial networks,

[0050] 3) Enabling IOT (Internet of Things) and M2M (Machine to Machine) communication

[0051] 4) High bandwidth, high data rate

[0052] On the other hand;

[0053] 1 ) Challenges related to propagation delay,

[0054] 2) Closed-loop link adaptation procedure,

[0055] 3) adapting to diverse channel conditions, can be listed as crucial in terms of performance of NTN.

[0056] The method developed by the invention is suitable for use with a wireless communication for Non-Terrestrial Networks (NTN).

[0057] The main object of the invention is to provide to determine anomaly zones in NTN access point coverage area and applying link adaptation according to anomaly zones. In this way, continuity of communication is ensured and there is no interruption in communication. Moreover, there is no need to use more uplink signal connections than necessary. This case provides to gain from the process processing time. Once the required signal environments for the user are determined, they can be easily provided in line with the user's needs.

[0058] This invention provides to enhance link adaptation for faded environments. Thanks to the invention, there is no battery problem for UE and there is no uplink link failure. The other object that is trying to increase the accuracy by trying to reduce the statistical variance with static and investigate the reports (power and channel reports).

[0059] The invention disclosure aims to address the three specified issues while simultaneously mapping both static and dynamic power consumption profiles of the environment, providing information to wireless nodes for the relevant zones. This way, obtaining a more robust link for frequency-selective channels and gathering information about the location, speed, and power consumption of dynamic objects, enabling power adjustments or modulation level changes for wireless nodes. As a result of these operations, the error probability will improve, . Furthermore, we will provide a solution to the uplink beam alignment issue for fast-changing channels and frequency-selective environments, tailored to the zones of interest.

[0060] In the other aspect, the embodiment of the present application provides a method, which can be executed by a network device, or by a component of the network device (such as a processor, a chip, or a chip system, etc.), or can be implemented by all or logical modules or software implementations of some network device functions or computer implemented device.

[0061] The method proposed by the embodiment of the present application can be applied to the 5G, 5G beyond, 6G or similar networks.

[0062] In this invention, sensing to determine a static and dynamic map of anomaly zones can be exploited. Thus, it is possible to enable dynamic link adaptation and share the knowledge of link adaptation outputs to the users. Also, it can be realized beam steering operation.

[0063] At the end of processes, through this invention that makes it possible to enhance the communication performance by

[0064] • Reducing latency,

[0065] • Reducing extra power consumption,

[0066] • Reducing process time and load, via anomaly zone(s),

[0067] • Increasing communication performance (like Qos), • Obtaining more resilient link to avoid problems in challenging environments, towards large scale fading and small scale fading characteristics of the communication channel especially at Doppler spread environments as stated at TS38.81 1 of 3GPP.

[0068] Thanks to the method, it is possible to fast connection by latency drops. It does not need to use additional power consumption, frequency-selective channels, fast fading channels such as fast fading allow fast link adaptation.

[0069] To achieve all the objects mentioned above and that will emerge from the following detailed description.

[0070] BRIEF DESCRIPTION OF THE DRAWINGS

[0071] The present disclosure, in accordance with one or more various examples, is described in detail with reference to the following figures. The drawings are provided for purposes of illustration only and merely depict examples of the disclosure. These drawings are provided to facilitate the reader's understanding of the disclosure and should not be considered limiting the breadth, scope, or applicability of the disclosure. It should be noted that for clarity and ease of illustration these drawings are not necessarily made to scale.

[0072] Figure 1 : NTN Communication Scheme

[0073] Figure 2: The deriving of link adaptation map of anomaly zones for NTN link adaptation Figure 3: The flowchart of link adaptation process for NTN link adaptation

[0074] Figure 4: The continuation of the flow chart of link adaptation process for NTN link adaptation in figure 3.

[0075] Figure 5: System Overview

[0076] REFERENCE LIST

[0077] The reference numbers of the elements included in the figures are explained below.

[0078] 9 User equipment

[0079] 10 NTN communication scheme 1 1 NTN access point

[0080] 12 Coverage area

[0081] 13 wireless nodes

[0082] 15 Forested areas

[0083] 16 Uplink Signals

[0084] 20 NTN link adaptation

[0085] 21 NTN access point

[0086] 22 Coverage area of the NTN access point

[0087] 23 Anomaly zones

[0088] 25 The gateway

[0089] 26 The architecture of gNB

[0090] 27 Antenna

[0091] 28 RF front end components

[0092] 29 Analog to Digital converter

[0093] 30 Quadrature l / Q processor

[0094] 31 Memory module(s)

[0095] 32 Link adaptation map(s)

[0096] 33 Relevant zone(s)

[0097] 36 Feeder Link

[0098] 37 Baseband processor

[0099] DETAILED DESCRIPTION OF THE INVENTION

[0100] In this detailed description, the subject matter is explained with references to examples without forming any restrictive effect only to make the subject more understandable.

[0101] The proposed invention relates to a method for adaptive uplink link adaptation in NTN. System overview is shown in Figure 5. The invention focuses on a solution for the closed-loop link adaptation issue within Non-Terrestrial Networks (NTN).

[0102] A computer implemented method uplink link adaptation which is suitable for being used with a wireless communication network comprising • At least one access point which is comprising a non-terrestrial network (NTN) platform,

[0103] • At least one any user equipment (UE) (9) which is being connected to the base station via an NTN,

[0104] • At least one gateway unit which is comprising a network node,

[0105] • A request / an uplink signal from a user equipment (9) to transmit data to a nonterrestrial communication hub and to receive data from the non-terrestrial communication hub,

[0106] • At least one memory which is providing to saving the power reduction map, characterized in that the method comprising the following steps:

[0107] • Creating of channel state reports and / or power parameters (prior information) or the wireless nodes (13) connected to the network node by the uplink signals (16) (Example: gNB via uplink signals (16),

[0108] • Examination of power and / or channel reports by network node (Example: gNB),

[0109] • Determining anomaly zones (23) as a geographical based on the examination reports to the anomaly region threshold (threshold)l values determined by the network node (Example gNB),

[0110] • Gathering reports and uplink signals (16) from the wireless nodes in the anomaly zones (23) for processing in the network node,

[0111] • Passing the uplink signals (16) through the detection and estimation methods (methods can be use any detection algorithms and any estimation algorithms in the prior art) and identifying the power reducing object by network node which may be located on gateway (25) (Example: gateway (25)),

[0112] • Estimating of Key Performance Indicator’s (KPI’s) for sensing measurements (range, velocity, angle of arrival position, height and / or power reduction levels (SINR)),

[0113] • Evaluating the results along with reports using statistical or artificial intelligence (Al) based methods (it can be any statistical or artificial intelligence (Al) algorithms) to increase accuracy in network node,

[0114] • Continuing to iteratively collect uplink signals (16) and reports to enhance accuracy based on the determined reliability parameter by network node (Example: gNB), • Processing data to increase statistical reliability by network node (Example: gNB),

[0115] • Checking the reliability levels (such as variance, covariance correlation coefficient) compared to the system reliability threshold (threshold2) level defined by the network node (Example: gNB) in each iteration,

[0116] • If there is not a predefined desired levels between reliability level and from the threshold2 (system reliability threshold) level defined by the network node in each iteration, (In other words, if there is not a considerable difference levels from the threshold2 level defined by the network node), continuing to iteratively collect uplink signals (16) and reports to enhance accuracy based on the determined reliability parameter by the network node and processing data to increase statistical reliability ( Note : Considerable difference level term will be adjusted by the network node and depends on both reliability parameters like variance, covariance and / or correlation coefficients and system model including anomaly zone(s), number of wireless nodes, traffic. In other words, considerable difference levels mean that is the predefined desired levels by network node),

[0117] • If there are predefined desired levels between reliability level and from the System reliability threshold (threshold2) level defined by the network node in each iteration, (If there is not a considerable difference from the threshold Ievel2 defined by the network node, continue to iteratively, (Note : Considerable difference level term will be adjusted by network node and depends on both reliability parameters like variance, covariance and / or correlation coefficients and system model including anomaly zone(s), number of wireless nodes, traffic. On the other hand, considerable difference means that is the predefined desired level by network node.)

[0118] • Checking mobile target within the map that reaches the speed and power reduction parameters defined by the network node (Example: gNB),

[0119] • If there is not a mobile target within the map that reaches the speed and power reduction parameters defined by the network node (Example: gNB), creating power reduction maps for each anomaly zone and informing wireless nodes approaching the relevant power reduction points about the required adaptive coded modulation (ACM) level and power level,

[0120] • Saving the power reduction map in memory, • If there is a mobile target within the map that reaches the speed and power reduction parameters defined by the network node (Example: gNB), determining the power reduction levels, velocities and locations of moving targets,

[0121] • Verification of location Global Navigation Satellite System (GNSS) information (If this information is already available, it will be transferred to the network node (gNB)) is available on the targets (Vehicle, Car, UE etc.) depending on whether GNSS receivers occur at the targets or not,

[0122] • Obtaining dynamic power reduction maps involving mobile objects by network node,

[0123] • Checking any change in performance criterions of anomaly zone(s) identified by network node (Example: gNB) in the channel and power reports obtained from the anomaly zones (23),

[0124] • If there is not any change in system performance identified by the network node (Example: gNB) in the channel and power reports obtained from the anomaly zones (23), stopping of process,

[0125] • If there is any change in system performance identified by the network node (Example: gNB) in the channel and power reports obtained from the anomaly zones (23), repeat the process starting from the beginning.

[0126] Threshold 1 (Anomaly region threshold):

[0127] Threshold 1 is actually Target RX power. In the equation below, if Target RX power is not at the desired value, we call it an anomaly. Details are given below.

[0128] Tx Power=Target Rx Power+PathLossFactor+MCS Factor+RB Factor+Power Control Command

[0129] Here;

[0130] Tx Power: The channel power of an Uplink physical channel to be transmitted. Such as; PRACH power, PUSCH power, PUCCH power, SRS Power.

[0131] Target Rx Power: This is a power that gNB requires for the safe decoding for the received signal. The power value is adjusted by the gNB. Such as, preambleReceivedTargetPower for PRACH, nominalWithoutGrant for PUSCH. If this power is very high, in general the UE transmission power would be high and it may be easier for gNB to decode the received channel if there is only one UE. But since this value is applicable to many UEs connected to the gNB, every UE would transmit high power when the multiple UEs are connected. As a result, the interference among the transmitted signals from many different UEs gets serious, and eventually gNB would suffer more from decoding failure.

[0132] For instance, PRACH channel's Preamble Received Target Power calculation is defined in the Medium Access Control (MAC) protocol document with the specification code TS 38.321 . It is specified in section 5.1 .3 of this document. It is adjusted by the Radio Resource Control.

[0133] Pathloss Factor: As the name implies, this is the factor coming from the pathloss between UE and gNB. It is adjusted by the Radio Resource Control.

[0134] MCS Factor (Modulation Coding Scheme): As the name implies, this is the factor determined by the MCS value for the channel to be transmitted. It is determined by DCI (Downlink Control Information)

[0135] The MCS value is defined in the document with the specification number TS 38.214, titled 'Physical layer procedures for data.' Depending on the selected MCS value parameter, the MCS factor value will vary. This variation will impact the required output power level for the selected uplink channel.

[0136] RB Factor (Resource Block): this is the factor determined by the number of RB being used for the channel to be transmitted. It is determined by DCI (Downlink Control Information)

[0137] Power Control Command: this is the factor to be determined by a specific value from gNB notified to UE. It is determined by DCI (Downlink Control Information)

[0138] There are four different uplink channels defined in the 3GPP TS 38.213 V17.6.0 Physical layer procedures for control document: PRACH (Physical Random Access Channel), PUCCH (Physical Uplink Control Channel), PUSCH (Physical Uplink Shared Channel), and SRS (Sounding Reference Signals). Since each channel has different requirements, the value(s) of the parameters in the main equation, such as Target Rx Power, MCS factor, and RB factor, will vary. However, the gNB calculates, based on the specified formula and considering the transmission channel and requirements mentioned in the formula, how much power the gNB needs to obtain for this transmission scheme. If the obtained power level is lower than the desired power level, the gNB instructs the UE to either increase its power through the downlink channel or adjust the MCS factor or RB factor. Considering the interference intensity and limited resources, gNB performs these adjustments as it serves multiple UE’s.

[0139] Threshold 2 (System reliability threshold)

[0140] In this context, the purpose of determining a threshold level is to operate the system at a specific reliability level. The reliability level is obtained by statistically evaluating measurement results and reports together at each sampled time instance. These statistical parameters may include variance, covariance, and correlation parameters. The best reliability level obtained with the selected statistical parameter(s) at sampled time instances can be chosen as the threshold. For example, the maximum correlation coefficient obtained for correlation, or the minimum values obtained for variance or covariance, can be selected as the threshold. These threshold levels can be defined by the gNB.

[0141] The considerable difference level, to be defined by the gNB, is influenced by parameters such as the selected statistical parameters, the number of anomaly regions, the number of wireless nodes, gNB hardware capabilities, and the vertical application requirements of the wireless node. For instance, to determine the considerable difference level, the statistical distribution can be derived for the obtained statistical parameter. For a vertical application that requires a very high accuracy level (e.g., autonomous vehicles), a similarity threshold of 90% can be chosen as the considerable difference level. However, for vertical applications where a relatively lower accuracy level may suffice, and the channel shows less variability, this considerable level can be in the range of 50%. These values are provided for illustrative purposes and are not mandatory. Based on consideration of the foregoing technical solution, possible embodiments of the invention are as follows;

[0142] The method wherein said

[0143] • Access point is a NTN payload, spaceborne and / or airborne platforms, like low earth orbit (LEO), geosynchronous equatorial orbit (GEO), a medium earth orbit (MEO), high altitude platforms (HAPS), unmanned aerial vehicle (UAV) or drone but not limited to these examples,

[0144] • Network nodes are satellite or base stations which are comprising gNodeBs (gNB) or eNodeBs (eNB) but not limited to these examples,

[0145] • Network node is comprising the decision mechanisms like detector, estimator, tracker for that performs the sensing process. Network node can be located on access point or gateway (25). But in this scenario, assuming that the network node is on gateway,

[0146] • User equipment’s (UE’s) (9) (wireless nodes) are vehicle, mobile phone, drone but not limited to these examples.

[0147] • Wherein said gateway (25) is located on ground but not limited to these examples, (Gateway (25) can be anywhere in the coverage area (12)).

[0148] • wherein said power reports are reference signal received power (RSRP) and / or reference signal received quality (RSRQ) and / or received signal strength indicator (RSSI) report and channel reports like channel state information (CSI) including the parameters like Channel Quality Indicator (CQI), Precoding Matrix Indicators (PMI), rank indicator (Rl) obtained from the uplink channels of each user equipment (9).

[0149] In the invention, by analyzing power and channel reports from uplink signals (16), anomaly zones (23) can be detected compared to threshold levels. After determining anomaly zones (23), it is aimed to create a static power reduction map via both SINR, CSI reports and uplink signals (16). After determining anomaly zones (23), it is aimed to create a static power reduction map via both SINR, CSI reports and uplink signals (16). Statistical based decision mechanisms like statistical variance, covariance, correlation or Al based decision mechanisms operating iteratively through correlator results, can be utilized to determine the presence of power-reducing objects or their locations. In this manner, by analyzing each received signal the power-reducing objects in locations, like the form of state vector, that minimize covariance can be recognized. This process provides to access parameters such as angle of arrival, angle of departure, and GPS locations. After determining a static map of anomaly zones (23), if there is not mobility at the zone, it can be understood from CSI and doppler shift of signal, no processing signal in gateway (25) for the same zone. Gateway (25) will set resource blocks and power values to the UE’s existing in the same zone. If the mobility on the zone exists, then it is extracted a dynamic map of the same zone. Dynamic map can be extracted by analyzing doppler shift and power loss. So RCS analysis can be executed at the same zone as we know AoD. For nearly all the UE’s, AoD values will be similar. Thus, it can be shared to users both position and power reduction levels for dynamic objects to the UE’s locating at the same zone.

[0150] NTN communication scheme (10) is shown in figure 1 . NTN coverage area (12) is also shown in figure 1 as an example. Coverage area (12) can contain multiple different environments (tree, ... etc.) with different channel characteristics. Users can be a mobile phone, car, drone... etc. in the coverage area (12). Users call as a UE (user equipment (9))

[0151] The working mechanism of the invention is as follows.

[0152] There are users who want to connect access point and connect within the coverage area (12). Users connect with uplink signals (16). Receiving uplink signals (16), NTN provides information about the user’s environment by looking at CSI report, RSRP measurement, RSSI measurement parameters (and RSRQ and SINR). In this way, it is possible to say that the link to which this user is connected troubled link or a good link. These parameters are determined whether the link is good or bad (trouble) according to the threshold level determined. At this time, the gateway (25) (for instance gNB...etc) interprets the measured values.

[0153] In figure 1 , the number 15 element can call a forest areas (15). This type of areas has bad signal. According to the measurements, forest area or similar environments are separated as a bad signal. The separated areas shown in figure 2. It continues to receive signals. But the gateway (25) says that receiving the signal but let to map the environment where the bad signals are located here. Let to find the points that reduce the signal. It is possible to do that even increasing or decreasing the modulation level or power level of the users who will catch those points or pass through that environment. Thanks to invention, users can be informed as a tell them what to do in line as relevant zone(s) (33).

[0154] CSI, RSRP, RSRQ, RSSI, SINR reports are received. After arriving reports power reports (RSRP, RSRQ, RSSI), SINR and channel reports (CSI, raw signal and uplink signals (16) are received within itself. Then correlating them among themselves. After correlation, identifying the bad points (bad signals). There are reliability parameters specified by the gateway (25). How many times that need to send a signal can be Al- based or statistical according to reliability parameters specified by the gateway (25). Method tries to reduce the variance between measurements. When the variance falls below a certain level, it can be called as the ambient noise. Sending ambient information to users.

[0155] Looking of mobile objects such as train, car...etc. and determine how mobile the environment is with the reports. If there is no difference between the signals, receiving from the environment and the mapping or if it is lower than the specified threshold level, we do not examine the environment again. Thus, we gain from the process processing time.

[0156] There may be more than two bad environments. If there is movement in the environment, for example a train. The train uses too much signal in communication. It is possible that can understand signal information by using signal by reports (CSI, RSSI, RSRP, RSRQ reports). The raw signal and the GPS signal are received, how much power it consumes and whatever the direction of movement, there is a moving object approaching you, according to it, it changes its own transmission parameters, changes its beamforming, beam string. Updating the parameters of the users in coverage area (12). Then sending the matrices containing the power parameters and determining the motivation level, which is called resource block, to the users in the coverage area (12). Anomaly zone: According to the reports, the locations that are received from each signal lower than the threshold level determined are anomaly zones (23). The size of the zone may vary depending on the number of elements, number of users.

[0157] First the detection and then the estimation process of these parameters takes place. Range speed, angle of arrival position, limit (power reduction levels) these parameters. Processed the signals and obtained analysed results. The object that is trying to increase the accuracy by trying to reduce the statistical variant with static and investigate the reports.

[0158] Threshold: Observation time is the iteration time, variance is statistical, covariance matrices, you want the covariances to fall below a certain limit. In this invention, location and power detection is doing.

[0159] When examining Figure 1 , an NTN communication scheme (10) is shown. This figure can be considered as a framework upon which our concept is built. It's important to note that the conditions depicted here do not necessarily represent the specific conditions under which the invention idea will be realized.

[0160] In this illustration, there is an elliptically outlined coverage area (12) of an access point (1 1 ). This NTN access point (11 ) can take the form of satellites like GEO / LEO / MEO, High Altitude Platform Stations (HAPS), or drones. Within this coverage area (129), there are wireless nodes that seek to connect to the NTN access point (1 1 ), and these wireless nodes (13) may be connected to the network via PUCCH, PUSCH, or SRS channels.

[0161] The required link adaptation parameters may vary for the specified three different channels, PUCCH, PUSCH, or SRS. The channel needs for reliable communication in this disclosure may be determined by gNB and adjust link adaptation parameters with respect to channel requirement. The wireless nodes (14) within this coverage area (12) may experience large scale fading and / or small scale fading including Doppler Spread and / or delay spread at Doppler spread channels. Furthermore, as shown in Figure 1 , these wireless nodes (13) can be located within metropolitan areas or in regions with intense shadowing effects, such as forested areas (15). Uplink signals (16) are collected within the NTN access point (1 1 ), and for the adjustment of modulation levels and power levels, Uplink signals (16) are aggregated at the gateway (25). The gateway (25) unit may physically reside in different places such as data centers, network facilities, or specific geographical locations.

[0162] In this scenario, the gateway (25) collects uplink signals. It gains insight into the channel conditions of the wireless nodes based on power levels, such as RSRP / RSRQ / RSSI, and channel parameters like CSI obtained from the uplink channels of each wireless node. Additionally, through location-finding tools, like GNSS receivers, on the wireless nodes, the gateway (25) will have information about the location of the wireless nodes. Moreover, receiving signals from all the wireless nodes (13) connected to the network node and extracting the same measurements, the gateway (25) will be able to distinguish areas within the coverage zone where channel impairments are high. It will also have knowledge about whether the relevant channel experiences slow or fast fading and the degree of frequency selectivity. When examining Figure 2, the process of creating a link adaptation map for anomaly zones (23) in NTN link adaptation (20) can be observed. In this illustration, as shown in Figure 1 a symbolic scenario is shown that includes the NTN access point (1 1 ), the coverage area of the NTN access point (22), and the gateway (25). This figure serves as a symbolic representation to elucidate the invention concept.

[0163] In this scenario, let’s assume there are two different anomaly zones (23) within the coverage area of the NTN access point (22). A different number of anomaly zones (23) can also be present in the scenario.

[0164] As indicated in Figure 1 , to obtain these anomaly zones (23), the signals received from UEs are analysed by the gateway (25). Power and channel information obtained from UEs, along with RSRP / RSRQ / RSSI and / or CSI reports, can be acquired by the gateway (25). The gateway (25) having a threshold level defined for power and channel parameters can determine whether the channel conditions in which the relevant UE is located exhibit frequency selectivity and / or fast fading characteristics.

[0165] For example, in Figure 2, two different anomaly zones (23) are defined, and symbolically, three different UEs are depicted within these zones. It also seems that a wireless node is about to enter anomaly zones (23).

[0166] Let's assume that the block represented by anomaly zones (23) consists of a set of wireless nodes (13) with slow fading and frequency-selective channels. Also let’s assume that the block represented by another anomaly zones (23) consists of a set of wireless devices with fast fading and frequency selective channels. Such clusters can be defined as anomaly zones (23) for the wireless nodes (13). Anomaly zones (23) can be defined through reports generated on the gateway (25). Once the anomaly zones (23) are identified, the locations and power reduction levels of objects causing power reduction within these zones can be determined. To achieve this objective, raw uplink signals (16) obtained from wireless nodes (13) and power and channel reports, RSRP / RSRQ / RSSI and / or CSI reports, can be collected on the gateway (25) through the transfer of the network node to the gateway (25). Additionally, in anomaly zones (23) and another different / same anomaly zones (23), symbolically, signal degradation due to multipath fading or shadowing caused by objects has also been illustrated.

[0167] Also, in this illustration it is assumed that gNB is located on the gateway (25). So, the architecture of gNB (26) is shown. The number of antenna(s) (27) are present at the architecture of gNB (26) to obtain uplink raw signals from the network node. Then RF front end components (28) occur to down convert to IF or baseband level. This component may include LNA, mixer, local oscillator, low pass filter, IF amplifier. After RF front end, Analog to Digital converter (A / D) (29) may occur to obtain baseband digital signal. Then baseband processor (37), quadrature l / Q processor (30) may occur to process both uplink raw signals and power / channel reports (RSSI / RSRQ / RSRP, CSI). At the end of a baseband processor (37), it can be obtained a power reduction map of the objects causing power reduction for each zone. Then the outputs from the baseband processor (37) may be recorded to memory module(s) (31 ) for subsequent processes and to facilitate comparisons, as well as to transmit link adaptation maps (32) to the wireless nodes (13) in the relevant zones. At the end of the last process at the gateway (25), link adaptation map(s) (32) can be constituted from power reduction map by considering total resource blocks and conveyed to the wireless nodes (13) to the relevant zone(s) (33). This map(s) related to each zone may be divided into wireless nodes (13) in the zone(s) or to the wireless nodes about to enter the relevant zone(s) (33).

[0168] In the baseband processor (37) step; information about the positions and mobilities of power reduction points in anomaly zones (23) can be observed due to the changes of RF front ends of uplink signals which are time shifts, frequency shifts because of Doppler effect, amplitude reductions, Angle of Arrival (AoA) by analysing phase and amplitude values of antennas (27) at network node, Angle of Departure (AoD) degrees and known locations of wireless nodes (13).

[0169] Furthermore, by processing these similar signals from multiple UEs within the same anomaly zone using a detector like 2D correlator-based receiver, the reliability in determining the locations of power-reducing objects can be increased. Also, as another input of this type of detector is channel and power reports obtained by the gateway (25) from wireless nodes (13).

[0170] Additionally, gateway can evaluate statistically or with Al-based algorithms by comparing these two streams obtained through detector. Through this process, the locations of power-reducing objects can be identified. The aim of this step is to enhance the output of detector, so it can be obtained fine estimation for position, doppler and power reduction level.

[0171] In some embodiments, if further enhancement of the accuracy of the power reduction map is desired, uplink signals and channel / power reports can continue to be collected for the relevant zone throughout an optional number of iterations defined by the gateway. In this process model based or Al based fusion work may be executed to enhance accuracy of KPI’s for the same zone. In such a scenario, the process for the anomaly zone concludes as soon as it falls below the threshold determined by statistical parameters like variance, covariance or correlation. The obtained power reduction map is stored in memory. The signal processing process is halted until any changes occur in the channel and power reports are received from the same region. On the other hand, the zone can include mobile objects like cars or trains as illustrated in anomaly zones (23) in figure 2, mobility can be observed at the output of analysis and requisite link adaptation can be shared to the wireless nodes (13) before arriving object to the location of wireless nodes (13).

[0172] As a result of the analysis, the power reduction map and resource blocks to be assigned in these locations are shared with the wireless nodes already present in the relevant region or those entering the area to realize uplink link adaptation.

[0173] In Figure 3, the flowchart of NTN uplink link adaptation method in the baseband processor is shown.

[0174] The proposed adaptive uplink link adaptation in NTN. The method is dependent on computer implemented method. The method can be implemented by a processor of a network device.

[0175] References:

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Claims

CLAIMS1 . A computer implemented method for uplink link adaptation which is suitable for being used with a wireless communication network comprising• At least one access point which is comprising a non-terrestrial network (NTN),• At least one any user equipment (9) which is being connected to the base station via an NTN,• At least one gateway unit which is comprising a network node,• An uplink signal from a user equipment (9) to transmit data to a nonterrestrial communication hub and to receive data from the non-terrestrial communication hub,• At least one memory which is providing to saving the power reduction map, characterized in that the method comprising the following steps:• Creating of power parameters and / or channel state reports for the wireless nodes (13) connected to the network node by the uplink signals (16),• Examination of power and / or channel reports by network node,• Determining anomaly zones (23) as a geographical based on the examination reports to the anomaly region threshold values determined by network node,• Gathering reports and uplink signals (16) from the wireless nodes in the anomaly zones (23) for processing in the network node,• Passing the uplink signals (16) through the detect and estimation methods and identifying the power reducing object the power reducing object by network node,• Estimating of Key Performance Indicator’s (KPI’s) for detection for sensing measurements,• Evaluating the results along with reports using statistical or artificial intelligence (Al) based methods to increase accuracy,• Continuing to iteratively collect uplink signals (16) and reports to enhance accuracy based on the determined reliability parameter by network node,• Processing data to increase statistical reliability by network node,• Checking the reliability levels compared to the system reliability threshold level defined by the network node in each iteration,• If there is not a predefined desired levels between reliability level and from the system reliability threshold level defined by the network node in each iteration, continuing to iteratively collect uplink signals and reports to enhance accuracy based on the determined reliability parameter by the network node and processing data to increase statistical reliability,• If there are a predefined desired levels between reliability level and from the system reliability threshold level defined by the network node in each iteration,• Checking mobile target within the map that reaches the speed and power reduction parameters defined by the network node,• If there is not a mobile target within the map that reaches the speed and power reduction parameters defined by the network node, creating power reduction maps for each anomaly zone and informing wireless nodes (13) approaching the relevant power reduction points about the adaptive coded modulation (ACM) level and power level,• Saving the power reduction map in memory,• If there is a mobile target within the map that reaches the speed and power reduction parameters defined by the network node, determining the power reduction levels, velocities and locations of moving targets,• Verification of location Global Navigation Satellite System (GNSS) information is available on the targets depending on whether GNSS receivers occur at the targets or not,• Obtaining dynamic power reduction maps involving mobile objects by network node,• Checking any change in performance criterions of anomaly zone(s) identified by network node in the channel and power reports obtained from the anomaly zones (23),• If there is not any change in system performance identified by the network node in the channel and power reports obtained from the anomaly zones (23), stopping of process,• If there is any change in system performance identified by the network node in the channel and power reports obtained from the anomaly zones (23), repeat the process starting from the beginning.

2. The method of according to claim 1 , wherein said access point is a NTN payload, spaceborne and / or airborne platforms.

3. The method of according to claim 1 or claim 2, wherein said access point is low earth orbit (LEO), geosynchronous equatorial orbit (GEO), a medium Earth orbit (MEO) High altitude platforms (HAPS), unmanned aerial vehicle (UAV) or drone.

4. The method of according to claim 1 , wherein said network nodes are satellite or base station which is comprising gNodeBs (gNB) or eNodeBs (eNB).

5. The method of according to claim 1 , wherein said network node is comprising the decision mechanism for that performs the sensing process.

6. The method of according to claim 5, wherein said decision mechanisms are detector, estimator or tracker.

7. The method of according to claim 1 , wherein said user equipment’s (9) are vehicle, mobile phone, drone.

8. The method of according to claim 1 , wherein said gateway is located on access point or ground.

9. The method of according to claim 1 , wherein said power reports are Reference Signals Received Power (RSRP) and / or reference signal received quality (RSRQ) and / or received signal strength indicator (RSSI) report and channel reports like channel state information (CSI) including parameters like Channel Quality Indicator (CQI), Precoding Matrix Indicators (PMI), rank indicator (Rl) obtained from the uplink channels of each user equipment (9).

10. The method of according to claim 1 , wherein said reliability level is variance, covariance, correlation and / or coefficient.1 1. The method of according to claim 1 , wherein said sensing measurements are range, velocity, angle of arrival position, height and / or power reduction levels (SINR).

12. The method of according to claim 1 , wherein said network node is located on access point or gateway (25).

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