In this letter, we propose a robust beamforming and rate optimization algorithm to improve spectral efficiency and transmission robustness by applying rate-splitting multiple access (RSMA) in reconfigurable intelligent surface (RIS)-aided symbiotic radio systems. Specifically, RSMA is used to serve all primary receivers on the same spectrum resource. Then, we formulate an optimization problem to minimize the total transmit power via the phase shift matrix of RIS, the beamforming vector of the base station, and the common rate parameter. To deal with this non-convex problem, we present an iteration-based optimization algorithm based on successive convex approximation and the alternating optimization method. Simulation results demonstrate that the proposed algorithm has 17.2% reduction in transmission power and 6.58% increase in the common rate compared to the other algorithms.
{"title":"Robust Beamforming and Rate Optimization for RIS-Aided Symbiotic Radio Systems With RSMA","authors":"Yongjun Xu;Mingyang Wang;Yunjian Jia;Yi Jin;Ruiqian Ma;Yijie Mao;Chau Yuen","doi":"10.1109/LCOMM.2024.3451700","DOIUrl":"10.1109/LCOMM.2024.3451700","url":null,"abstract":"In this letter, we propose a robust beamforming and rate optimization algorithm to improve spectral efficiency and transmission robustness by applying rate-splitting multiple access (RSMA) in reconfigurable intelligent surface (RIS)-aided symbiotic radio systems. Specifically, RSMA is used to serve all primary receivers on the same spectrum resource. Then, we formulate an optimization problem to minimize the total transmit power via the phase shift matrix of RIS, the beamforming vector of the base station, and the common rate parameter. To deal with this non-convex problem, we present an iteration-based optimization algorithm based on successive convex approximation and the alternating optimization method. Simulation results demonstrate that the proposed algorithm has 17.2% reduction in transmission power and 6.58% increase in the common rate compared to the other algorithms.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"28 10","pages":"2328-2332"},"PeriodicalIF":3.7,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142190021","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-29DOI: 10.1109/LCOMM.2024.3451696
Junhan Xie;Chunbo Luo;Yang Luo
Terahertz (THz) and sub-THz communications are visioned as the key technologies for the next generation mobile networks (6G). However, the sub-millimeter wavelength of THz and the enlarged array aperture of ultra-massive MIMO increase the Rayleigh distance, thereby making the working coverage of THz systems cross the near-field and far-field. Meanwhile, the beam split issue arisen in THz beamforming significantly impacts the system performance. Although the beam split issue in the near-field and far-field has been studied separately, it still remains a significant challenge for seamless cross-field communications. In this letter, we propose a novel wideband THz cross-field communication scheme for multiple users. An alternating optimization algorithm is proposed to maximize the sum-rate, which decomposes the original non-convex problem into three subproblems. The solutions to these subproblems are obtained by successive convex approximation, fractional programming and majorization minimization techniques. Simulation results demonstrate that our proposed scheme can achieve cross-field communication effectively.
{"title":"Cross Near- and Far-Field Beamforming for Wideband Multi-User Terahertz Communications","authors":"Junhan Xie;Chunbo Luo;Yang Luo","doi":"10.1109/LCOMM.2024.3451696","DOIUrl":"10.1109/LCOMM.2024.3451696","url":null,"abstract":"Terahertz (THz) and sub-THz communications are visioned as the key technologies for the next generation mobile networks (6G). However, the sub-millimeter wavelength of THz and the enlarged array aperture of ultra-massive MIMO increase the Rayleigh distance, thereby making the working coverage of THz systems cross the near-field and far-field. Meanwhile, the beam split issue arisen in THz beamforming significantly impacts the system performance. Although the beam split issue in the near-field and far-field has been studied separately, it still remains a significant challenge for seamless cross-field communications. In this letter, we propose a novel wideband THz cross-field communication scheme for multiple users. An alternating optimization algorithm is proposed to maximize the sum-rate, which decomposes the original non-convex problem into three subproblems. The solutions to these subproblems are obtained by successive convex approximation, fractional programming and majorization minimization techniques. Simulation results demonstrate that our proposed scheme can achieve cross-field communication effectively.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"28 10","pages":"2397-2401"},"PeriodicalIF":3.7,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142190022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-29DOI: 10.1109/LCOMM.2024.3451702
Ali Asgher Mohammed;Mirza Wasay Baig;Muhammad Abdullah Sohail;Syed Asad Ullah;Haejoon Jung;Syed Ali Hassan
This letter investigates the uplink communication of an energy harvesting (EH)-enabled resource-constrained secondary device (RCSD) coexisting with primary devices in a cognitive radio-aided non-orthogonal multi-access (CR-NOMA) network. Assuming a non-linear EH model in practice, the data rate of the RCSD is maximized using deep reinforcement learning (DRL). We first derive the optimal solutions for the parameters of interest including the time-sharing coefficient and transmit power of the RCSD, using convex optimization and then implement the DRL to address a continuous action spaced optimization problem. To comprehensively assess the agent’s performance and adaptability, we implement various DRL algorithms and compare them under non-linear EH, which reveals their suitability in various scenarios, aiding in selecting the most effective approach.
{"title":"Navigating Boundaries in Quantifying Robustness: A DRL Expedition for Non-Linear Energy Harvesting IoT Networks","authors":"Ali Asgher Mohammed;Mirza Wasay Baig;Muhammad Abdullah Sohail;Syed Asad Ullah;Haejoon Jung;Syed Ali Hassan","doi":"10.1109/LCOMM.2024.3451702","DOIUrl":"10.1109/LCOMM.2024.3451702","url":null,"abstract":"This letter investigates the uplink communication of an energy harvesting (EH)-enabled resource-constrained secondary device (RCSD) coexisting with primary devices in a cognitive radio-aided non-orthogonal multi-access (CR-NOMA) network. Assuming a non-linear EH model in practice, the data rate of the RCSD is maximized using deep reinforcement learning (DRL). We first derive the optimal solutions for the parameters of interest including the time-sharing coefficient and transmit power of the RCSD, using convex optimization and then implement the DRL to address a continuous action spaced optimization problem. To comprehensively assess the agent’s performance and adaptability, we implement various DRL algorithms and compare them under non-linear EH, which reveals their suitability in various scenarios, aiding in selecting the most effective approach.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"28 10","pages":"2447-2451"},"PeriodicalIF":3.7,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142190018","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-28DOI: 10.1109/LCOMM.2024.3451182
Kangwei Qi;Qiong Wu;Pingyi Fan;Nan Cheng;Qiang Fan;Jiangzhou Wang
Vehicular edge computing (VEC) is an emerging technology that enables vehicles to perform high-intensity tasks by executing tasks locally or offloading them to nearby edge devices. However, obstacles may degrade the communications and incur communication interruptions, and thus the vehicle may not meet the requirement for task offloading. Reconfigurable intelligent surfaces (RIS) is introduced to support vehicle communication and provide an alternative communication path. The system performance can be improved by flexibly adjusting the phase-shift of the RIS. For RIS-assisted VEC system where tasks arrive randomly, we design a control scheme that considers offloading power, local power allocation and phase-shift optimization. To solve this non-convex problem, we propose a new deep reinforcement learning (DRL) framework that employs modified multi-agent deep deterministic policy gradient (MADDPG) approach to optimize the power allocation for vehicle users (VUs) and block coordinate descent (BCD) algorithm to optimize the phase-shift of the RIS. Simulation results show that our proposed scheme outperforms the centralized deep deterministic policy gradient (DDPG) scheme and random scheme.
{"title":"Reconfigurable Intelligent Surface Assisted VEC Based on Multi-Agent Reinforcement Learning","authors":"Kangwei Qi;Qiong Wu;Pingyi Fan;Nan Cheng;Qiang Fan;Jiangzhou Wang","doi":"10.1109/LCOMM.2024.3451182","DOIUrl":"10.1109/LCOMM.2024.3451182","url":null,"abstract":"Vehicular edge computing (VEC) is an emerging technology that enables vehicles to perform high-intensity tasks by executing tasks locally or offloading them to nearby edge devices. However, obstacles may degrade the communications and incur communication interruptions, and thus the vehicle may not meet the requirement for task offloading. Reconfigurable intelligent surfaces (RIS) is introduced to support vehicle communication and provide an alternative communication path. The system performance can be improved by flexibly adjusting the phase-shift of the RIS. For RIS-assisted VEC system where tasks arrive randomly, we design a control scheme that considers offloading power, local power allocation and phase-shift optimization. To solve this non-convex problem, we propose a new deep reinforcement learning (DRL) framework that employs modified multi-agent deep deterministic policy gradient (MADDPG) approach to optimize the power allocation for vehicle users (VUs) and block coordinate descent (BCD) algorithm to optimize the phase-shift of the RIS. Simulation results show that our proposed scheme outperforms the centralized deep deterministic policy gradient (DDPG) scheme and random scheme.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"28 10","pages":"2427-2431"},"PeriodicalIF":3.7,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142190025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-28DOI: 10.1109/LCOMM.2024.3451018
Ugrasen Singh;Olav Tirkkonen
We present a robust link-adaptation method to realize ultra-reliable and low-latency communications (URLLC) against flashlight, i.e., on-off interference. A robust link-adaptation method is presented based on the measured signal-to-interference plus noise ratio (SINR) at the URLLC user, which varies between the time when interference power is measured and the time of payload transmission. We obtain the statistical distribution of the change of SINRs between two consecutive time slots and devise backoff methods guaranteeing the reliability of transmissions against flashlight interference. We derive the average transmission rate over Rayleigh fading channels in the considered system model. We observe that in the presence of flashlight interference, a strict reliability requirement reduces the transmission rate to a small fraction of the best effort service rate. When increasing the number of antennas at both the serving and interfering transmitters, the increase in array gain is partially compromised by the increased backoff needed to guarantee reliability. All analytical results are verified via Monte Carlo simulation.
{"title":"Robust Link Adaptation in Multiantenna URLLC Systems With Flashlight Interference","authors":"Ugrasen Singh;Olav Tirkkonen","doi":"10.1109/LCOMM.2024.3451018","DOIUrl":"10.1109/LCOMM.2024.3451018","url":null,"abstract":"We present a robust link-adaptation method to realize ultra-reliable and low-latency communications (URLLC) against flashlight, i.e., on-off interference. A robust link-adaptation method is presented based on the measured signal-to-interference plus noise ratio (SINR) at the URLLC user, which varies between the time when interference power is measured and the time of payload transmission. We obtain the statistical distribution of the change of SINRs between two consecutive time slots and devise backoff methods guaranteeing the reliability of transmissions against flashlight interference. We derive the average transmission rate over Rayleigh fading channels in the considered system model. We observe that in the presence of flashlight interference, a strict reliability requirement reduces the transmission rate to a small fraction of the best effort service rate. When increasing the number of antennas at both the serving and interfering transmitters, the increase in array gain is partially compromised by the increased backoff needed to guarantee reliability. All analytical results are verified via Monte Carlo simulation.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"28 10","pages":"2432-2436"},"PeriodicalIF":3.7,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10654344","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142190024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-27DOI: 10.1109/LCOMM.2024.3450612
Jingpeng Gao;Geng Chen;Chen Shen
In an open electromagnetic environment, few-shot learning (FSL) has been widely used to recognize new classes of radar signals with few labeled data, which is needed in spectrum management or electronic reconnaissance systems for saving time and human resources. However, suffering from the distribution shift, existing methods minimizing the empirical risk on few labeled data may lead to model degradation on unseen data. We propose a Bayesian prototype learning (BPL) method for few-shot radar signal modulation recognition. Specifically, we design a Bayesian prototype (BP) learner that enhances generalization to unseen data, regularizing the prototype embedding space by modeling prototype learning as a variational inference problem. Furthermore, to transfer base class knowledge efficiently, we design a shallow-deep feature map fusion (SDF) block, combining feature maps from shallow and deep layers. Additionally, a class-covariance metric (CCM) is introduced to refine classification boundaries by considering intra-class distributions. Extensive experiments show the superiority of our method, achieving a recognition accuracy of 97.91% with 5 labeled data per class.
{"title":"Bayesian Prototype Learning for Few-Shot Radar Signal Intra-Pulse Modulation Recognition","authors":"Jingpeng Gao;Geng Chen;Chen Shen","doi":"10.1109/LCOMM.2024.3450612","DOIUrl":"10.1109/LCOMM.2024.3450612","url":null,"abstract":"In an open electromagnetic environment, few-shot learning (FSL) has been widely used to recognize new classes of radar signals with few labeled data, which is needed in spectrum management or electronic reconnaissance systems for saving time and human resources. However, suffering from the distribution shift, existing methods minimizing the empirical risk on few labeled data may lead to model degradation on unseen data. We propose a Bayesian prototype learning (BPL) method for few-shot radar signal modulation recognition. Specifically, we design a Bayesian prototype (BP) learner that enhances generalization to unseen data, regularizing the prototype embedding space by modeling prototype learning as a variational inference problem. Furthermore, to transfer base class knowledge efficiently, we design a shallow-deep feature map fusion (SDF) block, combining feature maps from shallow and deep layers. Additionally, a class-covariance metric (CCM) is introduced to refine classification boundaries by considering intra-class distributions. Extensive experiments show the superiority of our method, achieving a recognition accuracy of 97.91% with 5 labeled data per class.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"28 10","pages":"2362-2366"},"PeriodicalIF":3.7,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142190031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-27DOI: 10.1109/LCOMM.2024.3450598
Anbang Zhang;Shuaishuai Guo
This letter introduces a multi-rate task-oriented communication (MR-ToC) framework. This framework dynamically adapts to variations in affordable data rate within the communication pipeline. It conceptualizes communication pipelines as symmetric, discrete, memoryless channels. We employ a progressive learning strategy to train the system, comprising a nested codebook for encoding and task inference. This configuration allows for the adjustment of multiple rate levels in response to evolving channel conditions. The results from our experiments show that this system not only supports edge inference across various coding levels but also excels in adapting to variable communication environments.
{"title":"Learning Multi-Rate Task-Oriented Communications Over Symmetric Discrete Memoryless Channels","authors":"Anbang Zhang;Shuaishuai Guo","doi":"10.1109/LCOMM.2024.3450598","DOIUrl":"10.1109/LCOMM.2024.3450598","url":null,"abstract":"This letter introduces a multi-rate task-oriented communication (MR-ToC) framework. This framework dynamically adapts to variations in affordable data rate within the communication pipeline. It conceptualizes communication pipelines as symmetric, discrete, memoryless channels. We employ a progressive learning strategy to train the system, comprising a nested codebook for encoding and task inference. This configuration allows for the adjustment of multiple rate levels in response to evolving channel conditions. The results from our experiments show that this system not only supports edge inference across various coding levels but also excels in adapting to variable communication environments.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"28 10","pages":"2303-2307"},"PeriodicalIF":3.7,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142190026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-26DOI: 10.1109/LCOMM.2024.3450177
Prashant Sharma;Swaminathan R.;Deepshikha Singh
In this letter, we consider a recently introduced doubly inverted Gamma-Gamma (IGGG) turbulence channel model and analyze the performance of a multi-hop unmanned-aerial-vehicle (UAV)-based free space optics (FSO) communication system assuming a decode-and-forward (DF) relaying strategy. UAV-based FSO communication improves wireless connectivity, allowing flexible deployment to establish a line-of-sight (LoS) communication with ground-based nodes. The channel modeling incorporates atmospheric turbulence, non-zero boresight pointing errors, path loss, and angle of arrival (AoA) fluctuations. The closed-form expressions for the outage probability (OP), average bit error rate (ABER), and ergodic capacity (EC) are derived over the IGGG turbulence channel with non-zero boresight pointing errors. In addition, the diversity gain and outage/BER floor are calculated from the asymptotic analyses. To validate all the analytical expressions, Monte-Carlo simulations are conducted utilizing the IGGG turbulence channel model.
{"title":"Multi-Hop UAV-Based FSO System Over Doubly Inverted Gamma-Gamma Turbulence Channel","authors":"Prashant Sharma;Swaminathan R.;Deepshikha Singh","doi":"10.1109/LCOMM.2024.3450177","DOIUrl":"10.1109/LCOMM.2024.3450177","url":null,"abstract":"In this letter, we consider a recently introduced doubly inverted Gamma-Gamma (IGGG) turbulence channel model and analyze the performance of a multi-hop unmanned-aerial-vehicle (UAV)-based free space optics (FSO) communication system assuming a decode-and-forward (DF) relaying strategy. UAV-based FSO communication improves wireless connectivity, allowing flexible deployment to establish a line-of-sight (LoS) communication with ground-based nodes. The channel modeling incorporates atmospheric turbulence, non-zero boresight pointing errors, path loss, and angle of arrival (AoA) fluctuations. The closed-form expressions for the outage probability (OP), average bit error rate (ABER), and ergodic capacity (EC) are derived over the IGGG turbulence channel with non-zero boresight pointing errors. In addition, the diversity gain and outage/BER floor are calculated from the asymptotic analyses. To validate all the analytical expressions, Monte-Carlo simulations are conducted utilizing the IGGG turbulence channel model.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"28 10","pages":"2313-2317"},"PeriodicalIF":3.7,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142190027","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-26DOI: 10.1109/LCOMM.2024.3450127
Qi Meng;Hancheng Lu;Langtian Qin
Mobile edge computing (MEC) -based computational offloading can help age-sensitive devices handle their tasks and reduce the age of information (AoI) of tasks. However, the inherent randomness of wireless channels makes it challenging to realize AoI provisioning for age-sensitive services in MEC systems. To address this issue, we propose a statistical AoI-aware MEC system that incorporates a stochastic network calculus (SNC)-based statistical AoI provisioning theoretical framework to support the tail distribution analysis of AoI. Particularly, we derive the closed-form expression of upper-bounded statistical AoI violation probability. Based on our analytical work, we formulate an energy consumption minimization problem by jointly optimizing offloading strategy, power, and bandwidth allocation in the AoI-aware MEC system. To solve the intractable problem, we propose a dynamic joint optimization algorithm based on block coordinate descent. Extensive simulations show the proposed algorithm achieves at least 13.2% energy consumption reduction compared to the RLTBB, GCGH, and PA-fixedB algorithms.
{"title":"Energy Optimization in Statistical AoI-Aware MEC Systems","authors":"Qi Meng;Hancheng Lu;Langtian Qin","doi":"10.1109/LCOMM.2024.3450127","DOIUrl":"10.1109/LCOMM.2024.3450127","url":null,"abstract":"Mobile edge computing (MEC) -based computational offloading can help age-sensitive devices handle their tasks and reduce the age of information (AoI) of tasks. However, the inherent randomness of wireless channels makes it challenging to realize AoI provisioning for age-sensitive services in MEC systems. To address this issue, we propose a statistical AoI-aware MEC system that incorporates a stochastic network calculus (SNC)-based statistical AoI provisioning theoretical framework to support the tail distribution analysis of AoI. Particularly, we derive the closed-form expression of upper-bounded statistical AoI violation probability. Based on our analytical work, we formulate an energy consumption minimization problem by jointly optimizing offloading strategy, power, and bandwidth allocation in the AoI-aware MEC system. To solve the intractable problem, we propose a dynamic joint optimization algorithm based on block coordinate descent. Extensive simulations show the proposed algorithm achieves at least 13.2% energy consumption reduction compared to the RLTBB, GCGH, and PA-fixedB algorithms.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"28 10","pages":"2263-2267"},"PeriodicalIF":3.7,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142190030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-26DOI: 10.1109/LCOMM.2024.3448309
Yi Hu;Baoguo Yu;Zhixin Deng;Meiying Ou
The pulse patterns constructed with existing methods don’t perform well in hit property or in pattern number. Aimed at this problem, a new method to construct pulse patterns for multiple time-hopping (TH) pulsed pseudolites (PLs) is proposed. In the proposed method, first different groups of congruence codes are generated; next with the generated congruence codes, different TH slot index (THSI) base matrices are built; then according to the effective data to pseudorandom noise (PRN) code duration ratio of the PL signal, by means of selecting several different THSI base matrices and horizontally concatenating them into one, different THSI tables are formed; finally by way of concatenating each row of a formed THSI table into a sequence and further mapping each entry of the sequence into binary codes, different pulse patterns for different PLs are constructed. The final simulations show that compared with other similar pulse pattern construction methods, the proposed method can give better overall performance in hit property and pattern number, and this will bring more benefits for PL applications.
{"title":"Pulse Pattern Construction for Time-Hopping Pseudolites With the Generated Congruence Codes","authors":"Yi Hu;Baoguo Yu;Zhixin Deng;Meiying Ou","doi":"10.1109/LCOMM.2024.3448309","DOIUrl":"10.1109/LCOMM.2024.3448309","url":null,"abstract":"The pulse patterns constructed with existing methods don’t perform well in hit property or in pattern number. Aimed at this problem, a new method to construct pulse patterns for multiple time-hopping (TH) pulsed pseudolites (PLs) is proposed. In the proposed method, first different groups of congruence codes are generated; next with the generated congruence codes, different TH slot index (THSI) base matrices are built; then according to the effective data to pseudorandom noise (PRN) code duration ratio of the PL signal, by means of selecting several different THSI base matrices and horizontally concatenating them into one, different THSI tables are formed; finally by way of concatenating each row of a formed THSI table into a sequence and further mapping each entry of the sequence into binary codes, different pulse patterns for different PLs are constructed. The final simulations show that compared with other similar pulse pattern construction methods, the proposed method can give better overall performance in hit property and pattern number, and this will bring more benefits for PL applications.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"28 10","pages":"2228-2232"},"PeriodicalIF":3.7,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142190028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：