Real-time traffic in a cellular network varies over time and often shows tidal patterns, such as the day/night traffic pattern. With this characteristic, we can reduce the energy consumption of a cellular network by consolidating workloads spreading over the entire network to fewer Base Stations (BSs). In this work, we propose a BS sleeping strategy for a two-tier Heterogeneous Cellular Network (HeCN) that consists of Macro Base Stations (MaBS) and Micro Base Stations (MiBS). We first use a Bidirectional Long Short-Term Memory (BLSTM) neural network to predict the future traffic of each user. Based on the predicted traffic, our proposed BS sleeping strategy switches user connections from underutilized MiBSs to other BSs, then switches off the idle MiBSs. The MaBSs are never switched off. All user connections have predefined Signal-to-Interference-plus-Noise Ratio thresholds, and we ensure that each user’s service quality, which is related to the user’s traffic demand rate, is not degraded when switching user connections. We demonstrate the effectiveness and superiority of our proposed strategy over four other baselines through extensive numerical simulations, where our proposed strategy substantially outperforms the four baselines in different scenarios.
{"title":"A Base Station Sleeping Strategy in Heterogeneous Cellular Networks Based on User Traffic Prediction","authors":"Xinyu Wang;Bingchen Lyu;Chao Guo;Jiahe Xu;Moshe Zukerman","doi":"10.1109/TGCN.2023.3324486","DOIUrl":"10.1109/TGCN.2023.3324486","url":null,"abstract":"Real-time traffic in a cellular network varies over time and often shows tidal patterns, such as the day/night traffic pattern. With this characteristic, we can reduce the energy consumption of a cellular network by consolidating workloads spreading over the entire network to fewer Base Stations (BSs). In this work, we propose a BS sleeping strategy for a two-tier Heterogeneous Cellular Network (HeCN) that consists of Macro Base Stations (MaBS) and Micro Base Stations (MiBS). We first use a Bidirectional Long Short-Term Memory (BLSTM) neural network to predict the future traffic of each user. Based on the predicted traffic, our proposed BS sleeping strategy switches user connections from underutilized MiBSs to other BSs, then switches off the idle MiBSs. The MaBSs are never switched off. All user connections have predefined Signal-to-Interference-plus-Noise Ratio thresholds, and we ensure that each user’s service quality, which is related to the user’s traffic demand rate, is not degraded when switching user connections. We demonstrate the effectiveness and superiority of our proposed strategy over four other baselines through extensive numerical simulations, where our proposed strategy substantially outperforms the four baselines in different scenarios.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136303585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2023-10-13DOI: 10.1109/TGCN.2023.3324205
Yang Lu;Ming-Min Zhao;Ming Lei;Min-Jian Zhao
Due to the sequential nature of the successive-cancellation (SC) algorithm, the decoding of polar codes suffers from significant decoding latencies, which hinders its application in low-latency communication scenarios. Fast SC decoding is able to speed up the SC decoding process, by implementing parallel decoders at the intermediate levels of the SC decoding tree for some special polar constituent subcodes (special nodes) with specific information and frozen bit patterns. To further improve the parallelism of SC decoding, this paper presents a new class of special nodes composed of a sequence of rate one or single-parity-check (SR1/SPC) nodes, which can be easily found especially in high-rate polar code and is able to envelop a wide variety of existing special node types. Then, we analyse the parity constraints caused by the frozen bits in each descendant node, such that the estimated codeword of the SR1/SPC node can keep its validity once the parity constraints are satisfied. Inspired by maximum-likelihood (ML) decoding, a generalized fast decoding algorithm is finally proposed to decode SR1/SPC nodes efficiently, which is able to guarantee that all the parity constraints are satisfied. Simulation results show that some SR1/SPC nodes can be decoded with quasi-ML performance, and the overall decoding latency can be reduced by up to 43.8% with slight performance improvement, as compared to the state-of-the-art fast SC decoder.
{"title":"Fast Successive-Cancellation Decoding of Polar Codes With Sequence Nodes","authors":"Yang Lu;Ming-Min Zhao;Ming Lei;Min-Jian Zhao","doi":"10.1109/TGCN.2023.3324205","DOIUrl":"10.1109/TGCN.2023.3324205","url":null,"abstract":"Due to the sequential nature of the successive-cancellation (SC) algorithm, the decoding of polar codes suffers from significant decoding latencies, which hinders its application in low-latency communication scenarios. Fast SC decoding is able to speed up the SC decoding process, by implementing parallel decoders at the intermediate levels of the SC decoding tree for some special polar constituent subcodes (special nodes) with specific information and frozen bit patterns. To further improve the parallelism of SC decoding, this paper presents a new class of special nodes composed of a sequence of rate one or single-parity-check (SR1/SPC) nodes, which can be easily found especially in high-rate polar code and is able to envelop a wide variety of existing special node types. Then, we analyse the parity constraints caused by the frozen bits in each descendant node, such that the estimated codeword of the SR1/SPC node can keep its validity once the parity constraints are satisfied. Inspired by maximum-likelihood (ML) decoding, a generalized fast decoding algorithm is finally proposed to decode SR1/SPC nodes efficiently, which is able to guarantee that all the parity constraints are satisfied. Simulation results show that some SR1/SPC nodes can be decoded with quasi-ML performance, and the overall decoding latency can be reduced by up to 43.8% with slight performance improvement, as compared to the state-of-the-art fast SC decoder.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136305811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2023-10-06DOI: 10.1109/TGCN.2023.3322539
Yijun Piao;Tae-Jin Lee
Since massive number of User Equipment (UE)s will cause more collisions and increase delay, improved Random Access (RA) methods have been researched and proposed. With the introduction of the new two step RA procedure in 3rd Generation Partnership Project (3GPP) Release 16, the average RA delay of UE could be further reduced. To further enhance two step RA in association with four step RA, we propose a new RA method that integrates four step RA and two step RA for heterogeneous IoT devices, so that UEs can perform two types of RA methods in parallel. With the proposed method, we aim to minimize the UE conflicts with the available RA resources, increasing the efficiency of RA and decreasing the average RA delay. We optimize the probability of two step RA in the proposed method and present algorithm to provide the optimal resource configuration and parameter settings in the RA procedure according to the RA status of UEs. A Markov chain model is formulated to analyze and confirm the effectiveness of the proposed RA method. As a result of extensive simulations, we present that the proposed RA method can enhance the property of the RA procedure for massive and heterogeneous devices access scenarios in 5G and 6G communications.
由于大量的用户设备（UE）会导致更多的碰撞并增加延迟，因此人们研究并提出了改进的随机接入（RA）方法。随着第三代合作伙伴计划（3GPP）第 16 版引入新的两步 RA 程序，UE 的平均 RA 时延可进一步降低。为了进一步加强两步 RA 与四步 RA 的结合，我们针对异构物联网设备提出了一种整合了四步 RA 和两步 RA 的新 RA 方法，使 UE 可以并行执行两种 RA 方法。通过所提出的方法，我们旨在最大限度地减少 UE 与可用 RA 资源的冲突，从而提高 RA 的效率并降低 RA 的平均延迟。我们优化了所提方法中两步 RA 的概率，并提出了一种算法，可根据 UE 的 RA 状态在 RA 过程中提供最优资源配置和参数设置。建立了马尔可夫链模型来分析和确认拟议 RA 方法的有效性。通过大量仿真，我们发现所提出的 RA 方法可以增强 5G 和 6G 通信中大规模和异构设备接入场景下 RA 程序的性能。
{"title":"Integrated 2–4 Step Random Access for Heterogeneous and Massive IoT Devices","authors":"Yijun Piao;Tae-Jin Lee","doi":"10.1109/TGCN.2023.3322539","DOIUrl":"10.1109/TGCN.2023.3322539","url":null,"abstract":"Since massive number of User Equipment (UE)s will cause more collisions and increase delay, improved Random Access (RA) methods have been researched and proposed. With the introduction of the new two step RA procedure in 3rd Generation Partnership Project (3GPP) Release 16, the average RA delay of UE could be further reduced. To further enhance two step RA in association with four step RA, we propose a new RA method that integrates four step RA and two step RA for heterogeneous IoT devices, so that UEs can perform two types of RA methods in parallel. With the proposed method, we aim to minimize the UE conflicts with the available RA resources, increasing the efficiency of RA and decreasing the average RA delay. We optimize the probability of two step RA in the proposed method and present algorithm to provide the optimal resource configuration and parameter settings in the RA procedure according to the RA status of UEs. A Markov chain model is formulated to analyze and confirm the effectiveness of the proposed RA method. As a result of extensive simulations, we present that the proposed RA method can enhance the property of the RA procedure for massive and heterogeneous devices access scenarios in 5G and 6G communications.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2023-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136008107","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2023-10-03DOI: 10.1109/TGCN.2023.3322096
Ali H. Abdollahi Bafghi;Mahtab Mirmohseni;Mohammad Reza Aref
In this paper, we study the problem of joint information and energy transfer in an ${M}$ -ary amplitude shift keying (ASK) two-hop channel with an energy harvesting relay. We consider two realistic assumptions; a finite battery size at the relay and energy loss in transmitting energy. We model the energy loss at the relay, where for sending an energy-containing symbol, the relay must receive multiple energy-containing symbols. Thus, we face a channel with memory. We model the energy saved in the battery as the channel state with the challenge that the receiver does not know the channel state. We propose two different achievable schemes, the first one is based on state-dependent superposition coding and the second one (for the binary case) is based on the equivalent timing channel approach. Both of our schemes are based on block Markov coding and backward decoding techniques. We derive achievable rates with single-letter expressions. In addition, we propose a single-letter upper bound for the system. In summary, the fundamental achievement of this work is proposing single-letter bounds for an energy harvesting relay with memory.
{"title":"On the Capacity of M-ary ASK Two-Hop Channel With Finite Battery Energy Harvesting Relay","authors":"Ali H. Abdollahi Bafghi;Mahtab Mirmohseni;Mohammad Reza Aref","doi":"10.1109/TGCN.2023.3322096","DOIUrl":"10.1109/TGCN.2023.3322096","url":null,"abstract":"In this paper, we study the problem of joint information and energy transfer in an \u0000<inline-formula> <tex-math>${M}$ </tex-math></inline-formula>\u0000-ary amplitude shift keying (ASK) two-hop channel with an energy harvesting relay. We consider two realistic assumptions; a finite battery size at the relay and energy loss in transmitting energy. We model the energy loss at the relay, where for sending an energy-containing symbol, the relay must receive multiple energy-containing symbols. Thus, we face a channel with memory. We model the energy saved in the battery as the channel state with the challenge that the receiver does not know the channel state. We propose two different achievable schemes, the first one is based on state-dependent superposition coding and the second one (for the binary case) is based on the equivalent timing channel approach. Both of our schemes are based on block Markov coding and backward decoding techniques. We derive achievable rates with single-letter expressions. In addition, we propose a single-letter upper bound for the system. In summary, the fundamental achievement of this work is proposing single-letter bounds for an energy harvesting relay with memory.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2023-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135913251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2023-10-02DOI: 10.1109/TGCN.2023.3321113
Xingyu Yuan;He Li;Kaoru Ota;Mianxiong Dong
Semantic segmentation is a critical area in computer vision, which needs voluminous image data streaming from user devices. Usually, it is challenging to process semantic segmentation tasks in user devices due to the Limited computation power and battery life. Intelligent edge computing effectively enhances the accuracy of semantic segmentation tasks by offloading computations to nearby devices, providing lower latency and improved responsiveness. However, inefficient offloading brings additional energy consumption due to the irregular relationship between task requirements and offloading settings. In this paper, we attempt to improve energy efficiency for processing semantic segmentation tasks in the edge environment by leveraging energy consumption and task requirements. We first investigate the power consumption with different offloading settings in a real intelligent edge environment. Based on the investigation, we formulate the offloading setting as a restricted multi-armed bandit problem and solve it by enhancing the upper confidence bound algorithm. Comprehensive simulation results show that the proposed solution significantly improves the energy efficiency for offloading semantic segmentation tasks in a given intelligent edge environment.
{"title":"Building Energy Efficient Semantic Segmentation in Intelligent Edge Computing","authors":"Xingyu Yuan;He Li;Kaoru Ota;Mianxiong Dong","doi":"10.1109/TGCN.2023.3321113","DOIUrl":"10.1109/TGCN.2023.3321113","url":null,"abstract":"Semantic segmentation is a critical area in computer vision, which needs voluminous image data streaming from user devices. Usually, it is challenging to process semantic segmentation tasks in user devices due to the Limited computation power and battery life. Intelligent edge computing effectively enhances the accuracy of semantic segmentation tasks by offloading computations to nearby devices, providing lower latency and improved responsiveness. However, inefficient offloading brings additional energy consumption due to the irregular relationship between task requirements and offloading settings. In this paper, we attempt to improve energy efficiency for processing semantic segmentation tasks in the edge environment by leveraging energy consumption and task requirements. We first investigate the power consumption with different offloading settings in a real intelligent edge environment. Based on the investigation, we formulate the offloading setting as a restricted multi-armed bandit problem and solve it by enhancing the upper confidence bound algorithm. Comprehensive simulation results show that the proposed solution significantly improves the energy efficiency for offloading semantic segmentation tasks in a given intelligent edge environment.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135844551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2023-10-02DOI: 10.1109/TGCN.2023.3321195
Haiyuan Li;Amin Emami;Karcius Day R. Assis;Antonis Vafeas;Ruizhi Yang;Reza Nejabati;Shuangyi Yan;Dimitra Simeonidou
Open Radio Access Network (Open RAN) has gained tremendous attention from industry and academia with decentralized baseband functions across multiple processing units located at different places. However, the ever-expanding scope of RANs, along with fluctuations in resource utilization across different locations and timeframes, necessitates the implementation of robust function management policies to minimize network energy consumption. Most recently developed strategies neglected the activation time and the required energy for the server activation process, while this process could offset the potential energy savings gained from server hibernation. Furthermore, user plane functions, which can be deployed on edge computing servers to provide low-latency services, have not been sufficiently considered. In this paper, a multi-agent deep reinforcement learning (DRL) based function deployment algorithm, coupled with a heuristic method, has been developed to minimize energy consumption while fulfilling multiple requests and adhering to latency and resource constraints. In an 8-MEC network, the DRL-based solution approaches the performance of the benchmark while offering up to 51% energy savings compared to existing approaches. In a larger network of 14-MEC, it maintains a 38% energy-saving advantage and ensures real-time response capabilities. Furthermore, this paper prototypes an Open RAN testbed to verify the feasibility of the proposed solution.
开放式无线接入网络（Open RAN）的基带功能分散在不同地点的多个处理单元上，因此受到业界和学术界的极大关注。然而，随着 RAN 范围的不断扩大，以及不同地点和时间段资源利用率的波动，有必要实施稳健的功能管理策略，以最大限度地降低网络能耗。最近开发的大多数策略都忽略了服务器激活过程的激活时间和所需能量，而这一过程可能会抵消服务器休眠带来的潜在节能效果。此外，可部署在边缘计算服务器上以提供低延迟服务的用户平面功能也未得到充分考虑。本文开发了一种基于多代理深度强化学习（DRL）的功能部署算法，该算法与启发式方法相结合，可在满足多个请求并遵守延迟和资源限制的同时最大限度地降低能耗。在 8-MEC 网络中，基于 DRL 的解决方案接近基准性能，同时与现有方法相比可节省高达 51% 的能源。在 14-MEC 的更大网络中，它保持了 38% 的节能优势，并确保了实时响应能力。此外，本文还制作了一个开放 RAN 测试平台原型，以验证所提解决方案的可行性。
{"title":"DRL-Based Energy-Efficient Baseband Function Deployments for Service-Oriented Open RAN","authors":"Haiyuan Li;Amin Emami;Karcius Day R. Assis;Antonis Vafeas;Ruizhi Yang;Reza Nejabati;Shuangyi Yan;Dimitra Simeonidou","doi":"10.1109/TGCN.2023.3321195","DOIUrl":"10.1109/TGCN.2023.3321195","url":null,"abstract":"Open Radio Access Network (Open RAN) has gained tremendous attention from industry and academia with decentralized baseband functions across multiple processing units located at different places. However, the ever-expanding scope of RANs, along with fluctuations in resource utilization across different locations and timeframes, necessitates the implementation of robust function management policies to minimize network energy consumption. Most recently developed strategies neglected the activation time and the required energy for the server activation process, while this process could offset the potential energy savings gained from server hibernation. Furthermore, user plane functions, which can be deployed on edge computing servers to provide low-latency services, have not been sufficiently considered. In this paper, a multi-agent deep reinforcement learning (DRL) based function deployment algorithm, coupled with a heuristic method, has been developed to minimize energy consumption while fulfilling multiple requests and adhering to latency and resource constraints. In an 8-MEC network, the DRL-based solution approaches the performance of the benchmark while offering up to 51% energy savings compared to existing approaches. In a larger network of 14-MEC, it maintains a 38% energy-saving advantage and ensures real-time response capabilities. Furthermore, this paper prototypes an Open RAN testbed to verify the feasibility of the proposed solution.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135845640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2023-10-02DOI: 10.1109/TGCN.2023.3321525
Khaled Humaid Altuwairgi;Ahmad Massud Tota Khel;Khairi Ashour Hamdi
This paper considers a reflecting surface (RS)-aided ambient backscatter communication (AmBC) system, where the RS can be either an intelligent RS (IRS) or a dumb RS (DRS). The former uses channel state information to apply phase shifts and form beams towards the reader, while the latter randomly reflects signals without applying phase shifts. The paper aims to evaluate the effects of ambient sources that act as simultaneous energy and interference sources, as well as the potential benefits of RSs on the bit error rate (BER) performance and coverage of AmBC systems. Therefore, it presents accurate BER expressions for on-off keying modulation using a simple non-coherent energy detection scheme under an IRS with ideal/non-ideal phase shifts and a DRS. Numerical and Monte-Carlo simulation results demonstrate that an IRS under both ideal and non-ideal phase shifts outperforms a DRS; however, the latter is cost-efficient and suitable for low-power applications, such as Internet of things communications. The results also show that an RS significantly enhances the limited coverage of conventional AmBC systems. Finally, it is observed that potential blockages limit the BER in the high-signal-to-noise ratio and large number of reflecting elements regimes, which can be improved by increasing the number of antennas.
{"title":"Energy Detection for Reflecting Surfaces-Aided Ambient Backscatter Communications","authors":"Khaled Humaid Altuwairgi;Ahmad Massud Tota Khel;Khairi Ashour Hamdi","doi":"10.1109/TGCN.2023.3321525","DOIUrl":"10.1109/TGCN.2023.3321525","url":null,"abstract":"This paper considers a reflecting surface (RS)-aided ambient backscatter communication (AmBC) system, where the RS can be either an intelligent RS (IRS) or a dumb RS (DRS). The former uses channel state information to apply phase shifts and form beams towards the reader, while the latter randomly reflects signals without applying phase shifts. The paper aims to evaluate the effects of ambient sources that act as simultaneous energy and interference sources, as well as the potential benefits of RSs on the bit error rate (BER) performance and coverage of AmBC systems. Therefore, it presents accurate BER expressions for on-off keying modulation using a simple non-coherent energy detection scheme under an IRS with ideal/non-ideal phase shifts and a DRS. Numerical and Monte-Carlo simulation results demonstrate that an IRS under both ideal and non-ideal phase shifts outperforms a DRS; however, the latter is cost-efficient and suitable for low-power applications, such as Internet of things communications. The results also show that an RS significantly enhances the limited coverage of conventional AmBC systems. Finally, it is observed that potential blockages limit the BER in the high-signal-to-noise ratio and large number of reflecting elements regimes, which can be improved by increasing the number of antennas.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135844230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2023-09-26DOI: 10.1109/TGCN.2023.3318986
Shuaishuai Guo;Jia Ye;Kaiqian Qu;Shuping Dang
Holographic multiple-input multiple-output (MIMO) communications are widely recognized as a promising candidate for the next-generation air interface. With holographic MIMO surface, the number of the spatial degrees-of-freedom (DoFs) considerably increases and also significantly varies as the user moves. To fully employ the large and varying number of spatial DoFs, the number of equipped RF chains has to be larger than or equal to the largest number of spatial DoFs. However, this causes much waste as radio frequency (RF) chains (especially the transmit RF chains) are costly and power-hungry. To avoid the heavy burden, this paper investigates green holographic MIMO communications with a few transmit RF chains under an electromagnetic-based communication model. We not only look at the fundamental capacity limits but also propose an effective transmission, namely non-uniform holographic pattern modulation (NUHPM), to achieve the capacity limit in the high signal-to-noise (SNR) regime. The analytical result sheds light on the green evaluation of MIMO communications, which can be realized by increasing the size of the antenna aperture without increasing the number of transmit RF chains. Numerical results are provided to verify our analysis and to show the great performance gain by employing the additional spatial DoFs as modulation resources.
{"title":"Green Holographic MIMO Communications With a Few Transmit Radio Frequency Chains","authors":"Shuaishuai Guo;Jia Ye;Kaiqian Qu;Shuping Dang","doi":"10.1109/TGCN.2023.3318986","DOIUrl":"10.1109/TGCN.2023.3318986","url":null,"abstract":"Holographic multiple-input multiple-output (MIMO) communications are widely recognized as a promising candidate for the next-generation air interface. With holographic MIMO surface, the number of the spatial degrees-of-freedom (DoFs) considerably increases and also significantly varies as the user moves. To fully employ the large and varying number of spatial DoFs, the number of equipped RF chains has to be larger than or equal to the largest number of spatial DoFs. However, this causes much waste as radio frequency (RF) chains (especially the transmit RF chains) are costly and power-hungry. To avoid the heavy burden, this paper investigates green holographic MIMO communications with a few transmit RF chains under an electromagnetic-based communication model. We not only look at the fundamental capacity limits but also propose an effective transmission, namely non-uniform holographic pattern modulation (NUHPM), to achieve the capacity limit in the high signal-to-noise (SNR) regime. The analytical result sheds light on the green evaluation of MIMO communications, which can be realized by increasing the size of the antenna aperture without increasing the number of transmit RF chains. Numerical results are provided to verify our analysis and to show the great performance gain by employing the additional spatial DoFs as modulation resources.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2023-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135750423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The next-generation networks are supposed to handle the large number of connections required for fifth-generation (5G) and beyond applications. Cooperative multi-relay communication with the downlink non-orthogonal multiple access (DL-NOMA) technique has the capability to provide increased energy and spectral efficiency (SE) by enabling such large connections. It promotes green communication by efficiently serving multiple users through a common resource and improving the system’s diversity without compromising the existing infrastructure. This paper investigates the performance of a multi-relay cooperative NOMA system to support 5G and beyond scenarios with practical impairments. The base station communicates with the NOMA end users using cooperative selective decode-and-forward (DF) based ${K}$ multiple relays and direct links. The asymptotic closed-form expression of the symbol error rate (SER) is derived for the NOMA users with imperfect channel state information (CSI) and successive interference cancellation (SIC) errors. The analysis is carried out for the generalized modulation pair, i.e., BPSK-BPSK, QPSK-BPSK and QPSK-QPSK, for NOMA end users. The efficacy of channel estimation error (CEE), power allocation coefficient and diversity order for the aforesaid system is also demonstrated. Finally, the theoretical analysis is endorsed by the Monte Carlo simulations.
{"title":"Performance of Selective DF-Based Multiple Relayed NOMA System With Imperfect CSI and SIC Errors","authors":"Sandhya Soni;Rahul Makkar;Divyang Rawal;Nikhil Sharma","doi":"10.1109/TGCN.2023.3319082","DOIUrl":"10.1109/TGCN.2023.3319082","url":null,"abstract":"The next-generation networks are supposed to handle the large number of connections required for fifth-generation (5G) and beyond applications. Cooperative multi-relay communication with the downlink non-orthogonal multiple access (DL-NOMA) technique has the capability to provide increased energy and spectral efficiency (SE) by enabling such large connections. It promotes green communication by efficiently serving multiple users through a common resource and improving the system’s diversity without compromising the existing infrastructure. This paper investigates the performance of a multi-relay cooperative NOMA system to support 5G and beyond scenarios with practical impairments. The base station communicates with the NOMA end users using cooperative selective decode-and-forward (DF) based \u0000<inline-formula> <tex-math>${K}$ </tex-math></inline-formula>\u0000 multiple relays and direct links. The asymptotic closed-form expression of the symbol error rate (SER) is derived for the NOMA users with imperfect channel state information (CSI) and successive interference cancellation (SIC) errors. The analysis is carried out for the generalized modulation pair, i.e., BPSK-BPSK, QPSK-BPSK and QPSK-QPSK, for NOMA end users. The efficacy of channel estimation error (CEE), power allocation coefficient and diversity order for the aforesaid system is also demonstrated. Finally, the theoretical analysis is endorsed by the Monte Carlo simulations.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2023-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135750426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2023-09-26DOI: 10.1109/TGCN.2023.3319437
Minseok Choi;Won Joon Yun;Seok Bin Son;Soohyun Park;Joongheon Kim
As mobile devices exhibit exceptional processing capabilities, super-resolution (SR) technology for video quality enhancement has developed. However, SR is still computationally-intensive, and the integration of SR into video streaming systems remains a nascent domain, with limited recent studies. To address this concern, we design an adaptive SR model that can dynamically control quality enhancement and computational demands in response to the available computational resources and input quality. Furthermore, we propose an integrated strategy for video segment delivery and resource allocation within video streaming systems aided by adaptive SR. This technique optimizes key parameters encompassing transmitter decisions (e.g., transcoding rate, the number of delivering segments, and transmit power) and receiver decisions (e.g., quality enhancement rate and computing resources). Our data-intensive simulation results demonstrate the adaptive SR-centric video streaming system that strikes a harmonious balance across diverse performance metrics. These metrics encompass average video quality, playback stall rates, transmission power, and computational resource consumption.
随着移动设备显示出卓越的处理能力，用于提高视频质量的超分辨率（SR）技术得到了发展。然而，超分辨率仍然是计算密集型技术，而且将超分辨率整合到视频流系统中仍然是一个新兴领域，近期的研究也很有限。针对这一问题，我们设计了一种自适应 SR 模型，该模型可根据可用计算资源和输入质量动态控制质量增强和计算需求。此外，我们还在自适应 SR 的帮助下，为视频流系统中的视频片段交付和资源分配提出了一种综合策略。该技术优化了关键参数，包括发射器决策（如转码率、传输段数量和发射功率）和接收器决策（如质量增强率和计算资源）。我们的数据密集型仿真结果表明，以 SR 为中心的自适应视频流系统在各种性能指标之间取得了和谐的平衡。这些指标包括平均视频质量、播放停滞率、传输功率和计算资源消耗。
{"title":"Joint Delay-Sensitive and Power-Efficient Quality Control of Dynamic Video Streaming Using Adaptive Super-Resolution","authors":"Minseok Choi;Won Joon Yun;Seok Bin Son;Soohyun Park;Joongheon Kim","doi":"10.1109/TGCN.2023.3319437","DOIUrl":"10.1109/TGCN.2023.3319437","url":null,"abstract":"As mobile devices exhibit exceptional processing capabilities, super-resolution (SR) technology for video quality enhancement has developed. However, SR is still computationally-intensive, and the integration of SR into video streaming systems remains a nascent domain, with limited recent studies. To address this concern, we design an adaptive SR model that can dynamically control quality enhancement and computational demands in response to the available computational resources and input quality. Furthermore, we propose an integrated strategy for video segment delivery and resource allocation within video streaming systems aided by adaptive SR. This technique optimizes key parameters encompassing transmitter decisions (e.g., transcoding rate, the number of delivering segments, and transmit power) and receiver decisions (e.g., quality enhancement rate and computing resources). Our data-intensive simulation results demonstrate the adaptive SR-centric video streaming system that strikes a harmonious balance across diverse performance metrics. These metrics encompass average video quality, playback stall rates, transmission power, and computational resource consumption.","PeriodicalId":13052,"journal":{"name":"IEEE Transactions on Green Communications and Networking","volume":null,"pages":null},"PeriodicalIF":4.8,"publicationDate":"2023-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135748508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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