Browsing by Author "Wu,Q."

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Citation Count: 1
Energy-Efficient Design for Reconfigurable Intelligent Surface Aided Cell-Free Ultra Dense HetNets
(Institute of Electrical and Electronics Engineers Inc., 2023) Panayırcı, Erdal; Hu,Y.; Dong,Z.; Panayirci,E.; Jiang,H.; Wu,Q.
In this article, we investigate the energy efficiency (EE) of reconfigurable intelligent surfaces (RISs) aided cell-free ultra-dense HetNets (CFUDN). To maximize the EE of CFUDN, users (UEs) association and clustering, RISs subsurface (SSF) associations are carefully designed. Then, the phase shift matrix of RISs and transmission power of base stations (BSs) are jointly optimized. Due to the non-convexity and high complexity of the formulated problem, this jointly optimized problem is usually difficult to solve. At present, the most commonly adopted method to deal with joint optimization problems is the block coordinate descent (BCD) algorithm based on an alternative optimization framework. However, as we all know, the BCD algorithm has some degree of performance loss due to the alternate optimization of variables. To overcome this challenging issue, a novel joint optimization framework based on Riemannian product manifolds (RPM) is proposed, in which the phase shift matrix of RISs and transmission power of BSs can be simultaneously optimized rather than alternating ways. The simulation results and computational complexity analysis demonstrate that the joint optimization framework based on the RPM exhibits superior performance and lower complexity compared to the joint optimization algorithm based on the BCD. © 2023 IEEE.
Citation Count: 0
Energy-Efficient Design for RIS-Aided Cell-Free Ultra Dense HetNets
(Institute of Electrical and Electronics Engineers Inc., 2023) Panayırcı, Erdal; Hu,Y.; Dong,Z.; Panayirci,E.; Jiang,H.; Wu,Q.
In this article, we investigate the energy efficiency of reconfigurable intelligent surfaces (RISs) aided full-duplex cellfree ultra dense hetNets (CFUDN), which has the advantages of both cell-free massive MIMO (CF-MMIMO) and ultra-dense hetNets (UDN). To maximize the EE of full-duplex CFUDN, users association and clustering, RISs subsurface associations are carefully designed. Then, the phase shift matrix of RISs and transmission power of base stations are jointly optimized. Due to the non-convexity and high complexity of formulated problem, it is extremely difficult to solve this problem. At present, the block coordinate descent (BCD) algorithm is the most commonly used method for joint optimization problems. However, as we all know, the BCD algorithm has some degree of performance loss due to alternate optimization. To overcome this challenging issue, a novel joint optimization framework based on Riemannian product manifolds (RPM) is proposed. © 2023 IEEE.
Energy-Efficient Secure Communication for Ios Aided Cfmmimo Network
(Institute of Electrical and Electronics Engineers Inc., 2024) Panayırcı, Erdal; Hu,Y.; Dong,Z.; Panayirci,E.; Jiang,H.; Wu,Q.
In this article, we investigate the security energy efficiency (SEE) of intelligent omni-surface (IOS) aided cellfree massive MIMO (CFMMIMO) networks. Firstly, we provide a SEE maximization design for the IOS-assisted CFMMIMO network. To address the formulated non-convex, multivariate problem, in particular, we first decouple the problem into two sub-problems, and design corresponding low-complexity algorithms for each sub-problem, including the joint optimization algorithm of the access point (AP) transmission beamforming and artificial noise covariance matrix based on semi-smooth Newton method (SSNM) as well as the joint optimization algorithm of IOS reflection-transmission phase shift matrix based on Riemannian product manifolds-conjugate gradient method (RPM-CG). The two subproblems are then iterated iteratively using the Block Coordinate Descent (BCD) algorithm to obtain the maximum SEE of the IOS-assisted CFMMIMO network. Simulation results show that the proposed algorithm outperforms the five baseline schemes in terms of SEE. © 2024 IEEE.
Citation Count: 0
Joint Resource Allocation in Multi-RIS and Massive MIMO Aided Cell-Free IoT Networks
(Institute of Electrical and Electronics Engineers Inc., 2024) Panayırcı, Erdal; Hu,Y.; Dong,Z.; Panayirci,E.; Jiang,H.; Wu,Q.
To meet the needs of high energy efficiency (EE) and various heterogeneous services for 6G, in this paper, we probe into the EE of reconfigurable intelligent surfaces (RISs) sub-surface (SSF) architecture-aided cell-free Internet of Things (CF-IoT) networks. Specifically, we jointly optimize the base station (BS)-RIS-IoT device (ID) joint associations, the RIS's phase shift matrix (PSM), and the BS's transmit power to enhance CF-IoT's EE. The elevated complexity (NP-hard) and non-convexity of the formulated problem pose significant challenges, making the solution highly difficult and intricate. To handle this challenging problem, we first develop an alternating optimization framework based on block coordinate descent, which can decouple the original problem into several subproblems. We then carefully design the corresponding low-complexity algorithm for each subproblem to solve it. Moreover, the proposed joint optimization framework serves as a versatile solution applicable to a wide range of scenarios aiming to maximize EE with the assistance of RISs. Simulations confirm that deploying RISs in CF-IoT scenarios is beneficial for improving the EE of the system, and the SSF architecture can further enhance the EE of the system. © 2014 IEEE.