Article
Engineering, Electrical & Electronic
Alireza Gholamrezaee, Hamid Farrokhi
Summary: This paper investigates a joint optimization problem of spectrum-efficient mode selection, fair sub-channel allocation, and power allocation of user pairs for a D2D-enabled MC-NOMA network. The optimization problem is first transformed into two sub-problems and solved using an enhanced three-side many-to-one matching algorithm and sequential convex programming method. The simulation results demonstrate the improved system performance of the proposed fair resource allocation algorithm.
DIGITAL SIGNAL PROCESSING
(2023)
Article
Chemistry, Analytical
Jie Zeng, Jiaying Sun, Yuxin Song, Jiajia Mei, Tiejun Lv, Shidong Zhou
Summary: This paper focuses on a user-centered NOMA collaboration system in an ultra-dense network and proposes two algorithms, a dynamic packet matching algorithm and an iterative algorithm based on convex functions. These algorithms improve system throughput while ensuring user quality of service.
Article
Computer Science, Information Systems
Minhoe Kim, Choong-Ho Cho, Byung Chang Chung
Summary: This paper proposes resource allocation schemes for a multi-carrier non-orthogonal multiple access (MC-NOMA) system with the consideration of energy harvesting. The schemes aim to maximize the total system capacity and ensure fairness among users, while guaranteeing minimum data rate and harvested energy for each user.
Article
Computer Science, Information Systems
Hongxiang Shao, Youming Sun, Zhiyong Du, Jihao Cai, Zhentao Duan
Summary: This paper investigates resource allocation for dense cloud non-orthogonal multiple access smallcell networks (NOMA SCN) with the aim of maximizing users' quality of service (QoE). A directed hypergraph is constructed to model the complex inter-interference relationship in cloud NOMA SCN. The QoE-oriented channel allocation and user pairing problem is formulated as a local cooperation game, which is proven to be an exact potential game. An optimal pure strategy Nash equilibrium (PNE) is identified in the proposed game to maximize network QoE level. A directed-hypergraph-based multi-agent learning algorithm is redesigned to achieve the optimal PNE. Simulation results are presented to validate the proposed learning scheme.
Article
Engineering, Electrical & Electronic
Sarah Basharat, Haris Pervaiz, Syed Ali Hassan, Rafay Iqbal Ansari, Haejoon Jung, Kapal Dev, Gaojian Huang
Summary: The paper investigates an IRS-aided NOMA system with the aim of maximizing the system sum rate while considering network QoS, rate fairness, and SIC constraints. A mixed non-convex problem is formulated, and a three-stage algorithm is proposed to solve it. Simulated results demonstrate the low complexity and superiority of the proposed resource allocation scheme.
PHYSICAL COMMUNICATION
(2022)
Article
Engineering, Electrical & Electronic
Sachin Trankatwar, Prashant Wali
Summary: In this study, the optimization of subchannel allocation (SA) and power allocation (PA) is proposed to maximize the sum rate of a multicarrier NOMA system. A minimum power gap constraint is imposed to enable successful successive interference cancellations (SIC) at the receiver. The WCF algorithm, combined with a low-complexity PA algorithm, achieves the best sum rate performance.
PHYSICAL COMMUNICATION
(2023)
Article
Chemistry, Multidisciplinary
Jun Li, Tong Gao, Bo He, Wenjing Zheng, Fei Lin
Summary: Non-orthogonal multiple access (NOMA) technology allows multiple users to share the same time-frequency resource for signal transmission, leading to improved spectral efficiency and throughput. This study focuses on user grouping and power allocation in the downlink of a multi-carrier NOMA system, with the optimization goal being the sum rate. The proposed step-by-step optimization method includes improving the user grouping approach to avoid grouping users with similar channel gains and utilizing a deep learning power allocation algorithm. The simulation results demonstrate that the deep learning power allocation method outperforms the fractional transmit power allocation and fixed power allocation methods, enhancing the system's sum rate by about 2.2% and 19%, respectively. Additionally, the power allocation methods proposed in this study achieve approximately a 10% improvement in the system's sum rate compared to the fractional transmit power allocation method used among subcarriers and between multiplexed users.
APPLIED SCIENCES-BASEL
(2023)
Article
Engineering, Electrical & Electronic
Jianglong Li, Xianfu Lei, Panagiotis D. Diamantoulakis, Lisheng Fan, George K. Karagiannidis
Summary: We investigate the physical layer security of a downlink cooperative non-orthogonal multiple access system with an untrusted relay. To improve the secrecy sum rate, a friendly jammer (FJ) is used. We formulate an optimization problem to maximize the secrecy sum rate by optimizing the power allocation at both the source and the FJ, and solve it iteratively using the alternating optimization method. We also study the secrecy sum rate of the proposed system with imperfect channel state information, and validate the effectiveness of the proposed FJ based schemes through simulation results.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Engineering, Electrical & Electronic
Wenbo Du, Tao Wang, Haijun Zhang, Dapeng Wu, Yumeng Li
Summary: This research focuses on a cellular unmanned-aerial-vehicle (UAV) system where multiple UAVs work together to transmit collected sensory data to a base station. The study investigates the resource allocation for the UAVs to maximize the system's energy efficiency. Simulation results show that the proposed scheme improves the uplink energy efficiency compared to the maximum power strategy.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Computer Science, Information Systems
Phu Lai, Qiang He, Feifei Chen, Mohamed Abdelrazek, John Hosking, John Grundy, Yun Yang
Summary: This study tackles the online user allocation problem in mobile edge computing systems. By using non-orthogonal multiple access, the aim is to minimize allocation delay and transmit power costs, thus increasing energy efficiency. The Lyapunov framework and a distributed game theory-based approach are adopted to achieve this objective and guarantee the data rate requirements of users over time.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2023)
Article
Computer Science, Hardware & Architecture
Yutong Wu, Jianyue Zhu, Xiao Chen, Yu Zhang, Yao Shi, Yaqin Xie
Summary: This paper proposes a quality-of-service-based SIC order method and optimizes power allocation for maximizing the rate in the uplink NOMA system. The simulation results demonstrate the superiority of the proposed method compared to traditional orthogonal multiple access and exhaustive search.
Article
Engineering, Electrical & Electronic
Wanli Ni, Xiao Liu, Yuanwei Liu, Hui Tian, Yue Chen
Summary: This article introduces a novel resource allocation framework for multi-cell intelligent reflecting surface (IRS) aided non-orthogonal multiple access (NOMA) networks. Numerical results demonstrate the significant increase in network sum rate with the use of IRS, higher energy efficiency of proposed algorithms for multi-cell IRS-aided NOMA networks, and the ability to adjust the balance between coverage area and spectrum efficiency by selecting the location of the IRS.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2021)
Article
Telecommunications
Ismail Cosandal, Mutlu Koca, Ezio Biglieri, Hikmet Sari
Summary: NOMA is a promising technique for accommodating data rate requirements of next generation networks, with PD-NOMA and NOMA-2000 being two implementations. In terms of outage probabilities, NOMA-2000 may significantly outperform PD-NOMA.
IEEE COMMUNICATIONS LETTERS
(2021)
Article
Computer Science, Hardware & Architecture
Mohammed W. Baidas
Summary: This paper addresses the resource allocation problem for multi-carrier clustered NOMA-enabled MEC networks, aiming to maximize network SOE through J-SA-PA-CRA. A low-complexity solution is proposed by decomposing the problem into two subproblems, which are optimally solved using a successive convex approximation algorithm and the KM algorithm, with the SMM algorithm proposed as a less complex alternative for sub-optimal subcarrier assignment. Simulation results confirm that the proposed solution efficiently achieves optimal (suboptimal) SOE compared to the global optimization package, outperforming OMA schemes like FDMA and TDMA.
Article
Engineering, Electrical & Electronic
Qiulei Huang, Wei Wang, Weidang Lu, Nan Zhao, Arumugam Nallanathan, Xianbin Wang
Summary: This paper proposes a scheme that combines NOMA and UAV to achieve better performance for wireless networks. It addresses the challenge of effective resource allocation for QoS provision in multi-cluster NOMA-UAV networks. The proposed scheme includes user clustering, optimal routing, and joint optimization of transmission power, hovering locations, and transmission duration. The non-convex problem is decomposed into three subproblems, with power and location optimizations transformed into convex problems. The duration optimization is solved directly as a linear programming problem. An iterative algorithm is then proposed to solve these subproblems alternately, and simulation results show the effectiveness of the proposed scheme.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2022)
Article
Computer Science, Artificial Intelligence
Rebekka Olsson Omslandseter, Lei Jiao, Yuanwei Liu, B. John Oommen
Summary: In this paper, a pioneering solution is presented to address the user grouping and power allocation problem in non-orthogonal multiple access (NOMA) systems. The proposed solution uses reinforcement learning-based approaches and object migration automaton to tackle the grouping problem without requiring prior knowledge. Simulation results demonstrate the effectiveness of the solution in handling dynamic channel coefficients.
PATTERN ANALYSIS AND APPLICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Chao Zhang, Wenqiang Yi, Yuanwei Liu, Lajos Hanzo
Summary: The new concept of Semi-ISaC is proposed for next-generation cellular networks, which allows for more flexibility in bandwidth allocation compared to the state-of-the-art. By investigating the evolution from OMA to NOMA, the proposed framework enhances the bandwidth efficiency. Analytical and simulation results show that Semi-ISaC has better channel capacity than conventional ISaC, and NOMA-based Semi-ISaC outperforms OMA-based Semi-ISaC.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Cunzhuo Zhao, Yuanwei Liu, Yunlong Cai, Minjian Zhao, Zhiguo Ding
Summary: In this work, the potential benefits of using unmanned aerial vehicles (UAVs) as aerial base stations (ABSs) and millimeter wave (mmWave) terrestrial base stations (TBSs) in a hybrid heterogeneous networks (HetNets) are explored. A flexible non-orthogonal multiple access (NOMA) based user association policy is proposed and analyzed using stochastic geometry. Numerical results confirm the superior performance of NOMA enabled HetNets compared with traditional orthogonal multiple access (OMA) enabled ABSs, and highlight the trade-off between association probabilities and spectrum efficiency.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Engineering, Electrical & Electronic
Jiakuo Zuo, Yuanwei Liu, Zhiguo Ding, Lingyang Song, H. Vincent Poor
Summary: Different from traditional reflection-only reconfigurable intelligent surfaces (RISs), simultaneously transmitting and reflecting RISs (STAR-RISs) extend the coverage from half-space to full-space by simultaneously transmitting and reflecting incident signals. In this paper, a novel STAR-RIS-assisted non-orthogonal multiple access (NOMA) system is proposed to maximize the achievable sum rate by jointly optimizing various parameters. A suboptimal two-layer iterative algorithm is proposed to tackle the non-convex problem with intricately coupled variables. Simulation results demonstrate the superiority of the proposed STAR-RIS-NOMA system over conventional RIS-NOMA and RIS-OMA systems.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2023)
Editorial Material
Engineering, Electrical & Electronic
Kunlun Wang, Yang Yang, Jiong Jin, Tao Zhang, Arumugam Nallanathan, Chintha Tellambura, Bijan Jabbari
Summary: Multi-tier computing enables flexible computation and communication resource sharing by offloading computation-intensive tasks to nearby servers along the cloud-to-thing continuum. It extends the traditional cloud computing architecture to the edge of the network by distributing computing, storage, and communication functions anywhere between the cloud and the endpoint. Multi-tier computing networks with heterogeneous computing resources and collaborative service architectures can support a full range of computing and networking services for different environments and applications.
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Zhixiong Chen, Wenqiang Yi, Yuanwei Liu, Arumugam Nallanathan
Summary: The proposed knowledge-aided FL framework allows for heterogeneous local models and reduces communication overhead in the training process. The convergence of the framework under non-convex loss functions is theoretically analyzed and an optimal solution for device scheduling, bandwidth allocation, and power control is derived. Experimental results show that the proposed KFL significantly reduces communication overhead while achieving better learning performance.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2023)
Article
Engineering, Multidisciplinary
Weidang Lu, Yandan Mo, Yunqi Feng, Yuan Gao, Nan Zhao, Yuan Wu, Arumugam Nallanathan
Summary: This paper proposes two secure transmission methods for multi-UAV-assisted mobile edge computing based on single-agent and multi-agent reinforcement learning, respectively. The deployment of UAVs is optimized using the spiral placement algorithm, and secure offloading is optimized using reinforcement learning to maximize system utility. Simulation results show that compared to the single-agent method and the benchmark, the multi-agent method can optimize offloading better and achieve larger system utility.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2023)
Article
Engineering, Electrical & Electronic
Yuhua Su, Xiaowei Pang, Weidang Lu, Nan Zhao, Xianbin Wang, Arumugam Nallanathan
Summary: This work investigates the potential of combining UAV and STAR-RIS in wireless networks for full-space coverage. A sum-rate maximization problem is formulated in STAR-RIS aided non-orthogonal multiple access UAV networks, and an efficient algorithm is proposed to obtain the suboptimal solution. Simulation results verify the superiority of the proposed scheme.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Engineering, Electrical & Electronic
Heng Wang, Haijun Zhang, Xiangnan Liu, Keping Long, Arumugam Nallanathan
Summary: Due to limited computation capacity of wireless user devices, multi-access edge computing (MEC) has become an effective way to meet the real-time demands. To increase system capacity, a UAV-assisted computation offloading architecture in the terahertz (THz) band is proposed. Deep reinforcement learning (DRL) based approaches, such as DDQN and DDPG, are used to solve the non-convex optimization problem of minimizing latency.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2023)
Article
Computer Science, Information Systems
Xiao-Ren Xu, Yi-Han Xu, Wen Zhou, Arumugam Nallanathan
Summary: This study investigates the resource allocation problem in Energy Harvesting-supported Cognitive Industrial Machine-to-Machine (EH-CI-M2M) network with the use of Unmanned Aerial Vehicles (UAVs) communication. The objective is to maximize the average energy efficiency by considering EH time slot assignment, transmit power control, and bandwidth allocation, while considering Quality of Service (QoS) and available energy status. The problem is approached through non-linear fractional programming and variable relaxation, and an iterative algorithm is proposed for optimization. Extensive simulation results demonstrate the superiority of the proposed scheme in terms of energy efficiency.
IEEE WIRELESS COMMUNICATIONS LETTERS
(2023)
Article
Computer Science, Information Systems
Chen Zhao, Xiaowei Pang, Weidang Lu, Yunfei Chen, Nan Zhao, Arumugam Nallanathan
Summary: This study proposes the utilization of intelligent reflecting surface (IRS) to improve the energy efficiency of unmanned aerial vehicle (UAV) transmission. By jointly optimizing UAV trajectory, transmit power, and IRS phase shifts based on statistical channel state information (CSI), the energy efficiency is maximized. The non-convex problem is decomposed into two sub-problems and solved iteratively to obtain an effective solution.
IEEE WIRELESS COMMUNICATIONS LETTERS
(2023)
Article
Engineering, Multidisciplinary
Shunpu Tang, Lunyuan Chen, Ke He, Junjuan Xia, Lisheng Fan, Arumugam Nallanathan
Summary: This paper investigates the deployment of computational intelligence and deep learning in edge-enabled industrial IoT networks. A multi-exit-based federated edge learning framework is proposed to address the limited resources issue. Simulation experiments show that the proposed framework achieves significant accuracy improvement in industrial IoT networks.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2023)
Proceedings Paper
Computer Science, Hardware & Architecture
Xinyu Gao, Wenqiang Yi, Alexandros Agapitos, Hao Wang, Yuanwei Liu
Summary: Coverage and capacity are important metrics for evaluating performance in wireless networks. However, there are conflicting relationships between coverage and capacity, such as the trade-off between transmit power and inter-cell interference. To balance coverage and capacity, a novel model is proposed for optimizing coverage and capacity in simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RISs) assisted networks. A machine learning-based multi-objective optimization algorithm, called the multi-objective proximal policy optimization (MO-PPO) algorithm, is proposed to solve the coverage and capacity optimization problem. The numerical results demonstrate that the investigated update strategy outperforms fixed weight-based multi-objective algorithms.
2023 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE, WCNC
(2023)
Article
Engineering, Electrical & Electronic
Xiaolan Liu, Jiadong Yu, Yuanwei Liu, Yue Gao, Toktam Mahmoodi, Sangarapillai Lambotharan, Danny Hin-Kwok Tsang
Summary: The increasing number of wireless devices and the large amount of data they generate in the internet of things have made cloud-based solutions inefficient. By combining edge computing and artificial intelligence, computation servers can be placed closer to the network edge, enabling intelligent decision-making and distributed machine learning. The deployment of AI techniques in wireless communications also leads to the concept of native AI wireless networks.
IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY
(2023)
Article
Engineering, Electrical & Electronic
Ruikang Zhong, Xidong Mu, Yuanwei Liu, Yue Chen, Jianhua Zhang, Ping Zhang
Summary: This paper proposes a novel framework for downlink non-orthogonal multiple access (NOMA) communication using reconfigurable intelligent surfaces (STAR-RISs). The STAR-RIS is divided into tiles, and a distributed learning approach is used for passive beamforming and power allocation. The simulation results show that the energy splitting (ES) protocol outperforms the mode switching (MS) protocol, and the tile-based passive beamforming approach is superior to benchmarks when the STAR-RIS is large. Additionally, the proposed access-free federated learning (AFFL) framework effectively reduces training overhead.
IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING
(2023)
