Panayırcı, ErdalLi,B.Hu,Y.Dong,Z.Panayirci,E.Jiang,H.Wu,Q.2024-06-232024-06-23202310018-9545https://doi.org/10.1109/TVT.2023.3325877https://hdl.handle.net/20.500.12469/5838In 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.eninfo:eu-repo/semantics/closedAccess6Gcell-free massive MIMORiemannian product manifold (RPM)RISultra-dense HetNetsArticle3767378537310.1109/TVT.2023.33258772-s2.0-85176319530Q1Q1