The Research On Radio Resource Management In Full Duplex Self-backhaul Based Small Cell Networks

With the emergence of new high-data-rate and low-latency traffic and the development of Internet of Things and Vehicular Networks, the current mo-bile communication networks are under tremendous pressure. This has pro-moted the research and development of the next generation mobile communica-tion networks (5G), to improve network capacity and end-to end performance.Small cell networks, by virtue of improving spectrum efficiency and energy efficiency substantially and reducing the network cost, have been one of the most promising technologies of 5G. However, currently the backhaul problem has been a bottleneck restricting large-scale deployment of small cell base sta-tions (SBSs). By using full duplex (FD) communication technology, FD self-backhaul technology achieves the SBSs' wireless backhaul on the pre-existing cellular spectrum without new hardware and spectrum, reducing the network cost. Therefore, FD self-backhaul has become one of promising technologies to solve the backhaul problem of small cell networks, and attracts many atten-tions of academy and industrial.At the same time, radio resource management plays a very important role in controlling interference, improving spectrum efficiency and energy efficiency,ensuring quality of service (QoS) in small cell networks. For those reasons,we will focus on radio resource management technologies in FD self-backhaul based small cell networks. In order to ensure the quality of backhaul links and obtain higher spectrum efficiency and energy efficiency, we propose several novel radio resource management algorithms to control interference, allocate spectrum and power resources reasonably, and choose the optimal access base station for users with jointly considering some other key technologies in 5G.The main contributions and innovations of this paper are as follows:(1) A distributed virtual resource allocation algorithm is put forward for the FD self-backhaul based small cell networks with wireless virtualizationFirstly, we introduce wireless virtualization into small cell networks, and propose a virtualized small cell network architecture. Secondly, we formu-late the virtual resource allocation problem in virtualized small cell networks with FD self-backhauls as an optimization problem, considering both the rev-enue earned by serving users and the cost paid to InPs for consuming power,spectrum, and backhaul resources. Then, to solve it efficiently, we divide the original problem into two subproblems. In the first subproblem, assuming the spectrum allocation factor is known, we transfer it to a convex optimization problem, and then solve it by an efficient alternating direction method of mul-tipliers (ADMM)-based distributed algorithm to get the user association and power allocation scheme. The second subproblem solves the spectrum alloca-tion factor based on the results of the first subproblem. By combining the solv-ing process of the two subproblems, we propose an ADMM-based distributed virtual allocation algorithm. Finally, simulations results show that we can take the advantages of both wireless network virtualization and FD self-backhauls with the proposed distributed virtual resource allocation algorithm. Infrastruc-ture Providers (InPs), Mobile Virtual Networks Operators (MVNOs), and users can benefit from the proposed resource allocation scheme.(2) A power allocation algorithm maximizing spectrum efficiency is pro-posed for the FD self-backhaul based small cell networks with massive Multiple Input Multiple Output (MIMO)Firstly, we propose a novel architecture of FD self-backhaul small cell networks with massive MIMO technology to achieve the transmissions of the access link of users and the backhaul link of SBSs simultaneously in the same frequency band, which improve spectrum efficiency and ensure the quality of self-backhaul. Secondly, we analyze the spectrum efficiency of users' access links and SBSs' backhaul links according to Shannon Equation, then we formu-late the power allocation problem of the macro base station (MBS) and SBSs as an optimization problem, which maximizes the total spectrum efficiency of the small cell networks. Thirdly, since the formulated problem is a non-convex optimization problem, its computational complexity is high. To solve it effi-ciently, we transform the original problem into a difference of convex program(DCP) by using successive convex approximation method (SCAM), and then solve it using a constrained concave convex procedure (CCCP)-based iterative algorithm. Furthermore, we prove the convergence of our proposed iteration al-gorithm. Finally, extensive simulations show the effectiveness of the proposed FD self-backhaul scheme with massive MIMO.(3) An energy efficient resource allocation algorithm is proposed for the FD self-backhaul based small cell networks with energy harvestingFirstly, we propose an architecture of small cell networks with FD self-backhaul and energy harvesting. In our proposed scheme, the MBS is powered by the traditional power grid, while the SBSs are powered by renewable en-ergy. This architecture achieves the self-backhaul and self-powering of SBSs,which reduces the network cost substantially and improves the deployment flex-ibility of SBSs. Secondly, we propose an advanced Block Digitalization (BD)precoding based interference cancellation method, cancelling inter-tier inter-ference and multi-user interference simultaneously, which improving spectrum efficiency and energy efficiency. Thirdly, to further improve the energy effi-ciency, we formulate the cell association and power allocation as an optimiza-tion problem from the energy efficiency perspective, taking into account the lowest QoS requirement of users, the energy arrival rate, and the remaining energy of SBSs. Next, since the formulated problem is non-convex, its compu-tational complexity is prohibitively high. To solve it efficiently, we transfer the original problem into a DCP by appropriate variable substitution, and then solve it via previous proposed algorithm. Finally, simulation results show our pro-posed scheme achieves good performance in terms of energy efficiency, energy consumption and cost, and ensure the effective operation of SBSs.