Resource Allocation for D2D Communications Based on Matching Theory

PhDDevice-to-device (D2D) communications underlaying a cellular infrastructure takes advantage of the physical proximity of communicating devices and increasing resource utilisation. However, adopting D2D communications in complex scenarios poses substantial challenges for the resource allocation design. Meanwhile, matching theory has emerged as a promising framework for wireless resource allocation which can overcome some limitations of game theory and optimisation. This thesis focuses on the resource allocation optimisation for D2D communications based on matching theory. First, resource allocation policy is designed for D2D communications underlaying cellular networks. A novel spectrum allocation algorithm based on many-to-many matching is proposed to improve system sum rate. Additionally, considering the quality-of-service (QoS) requirements and priorities of di erent applications, a context-aware resource allocation algorithm based on many-to-one matching is proposed, which is capable of providing remarkable performance enhancement in terms of improved data rate, decreased packet error rate (PER) and reduced delay. Second, to improve resource utilisation, joint subchannel and power allocation problem for D2D communications with non-orthogonal multiple access (NOMA) is studied. For the subchannel allocation, a novel algorithm based on the many-to-one matching is proposed for obtaining a suboptimal solution. Since the power allocation problem is non-convex, sequential convex programming is adopted to transform the original power allocation problem to a convex one. The proposed algorithm is shown to enhance the network sum rate and number of accessed users. Third, driven by the trend of heterogeneity of cells, the resource allocation problem for NOMA-enhanced D2D communications in heterogeneous networks (HetNets) is investigated. In such a scenario, the proposed resource allocation algorithm is able to closely approach the optimal solution within a limited number of iterations and achieves higher sum rate compared to traditional HetNets schemes. Thorough theoretical analysis is conducted in the development of all proposed algorithms, and performance of proposed algorithm is evaluated via comprehensive simulations. This thesis concludes that matching theory based resource allocation for D2D communications achieves near-optimal performance with acceptable complexity. In addition, the application of D2D communications in NOMA and HetNets can improve system performance in terms of sum rate and users connectivity

Advanced Technologies for Device-to-device Communications Underlaying Cellular Networks

The past few years have seen a major change in cellular networks, as explosive growth in data demands requires more and more network capacity and backhaul capability. New wireless technologies have been proposed to tackle these challenges. One of the emerging technologies is device-to-device (D2D) communications. It enables two cellular user equip- ment (UEs) in proximity to communicate with each other directly reusing cellular radio resources. In this case, D2D is able to of oad data traf c from central base stations (BSs) and signi cantly improve the spectrum ef ciency of a cellular network, and thus is one of the key technologies for the next generation cellular systems. Radio resource management (RRM) for D2D communications and how to effectively exploit the potential bene ts of D2D are two paramount challenges to D2D communications underlaying cellular networks. In this thesis, we focus on four problems related to these two challenges. In Chapter 2, we utilise the mixed integer non-linear programming (MINLP) to model and solve the RRM optimisation problems for D2D communications. Firstly we consider the RRM optimisation problem for D2D communications underlaying the single carrier frequency division multiple access (SC-FDMA) system and devise a heuristic sub- optimal solution to it. Then we propose an optimised RRM mechanism for multi-hop D2D communications with network coding (NC). NC has been proven as an ef cient technique to improve the throughput of ad-hoc networks and thus we apply it to multi-hop D2D communications. We devise an optimal solution to the RRM optimisation problem for multi-hop D2D communications with NC. In Chapter 3, we investigate how the location of the D2D transmitter in a cell may affect the RRM mechanism and the performance of D2D communications. We propose two optimised location-based RRM mechanisms for D2D, which maximise the throughput and the energy ef ciency of D2D, respectively. We show that, by considering the location information of the D2D transmitter, the MINLP problem of RRM for D2D communications can be transformed into a convex optimisation problem, which can be ef ciently solved by the method of Lagrangian multipliers. In Chapter 4, we propose a D2D-based P2P le sharing system, which is called Iunius. The Iunius system features: 1) a wireless P2P protocol based on Bittorrent protocol in the application layer; 2) a simple centralised routing mechanism for multi-hop D2D communications; 3) an interference cancellation technique for conventional cellular (CC) uplink communications; and 4) a radio resource management scheme to mitigate the interference between CC and D2D communications that share the cellular uplink radio resources while maximising the throughput of D2D communications. We show that with the properly designed application layer protocol and the optimised RRM for D2D communications, Iunius can signi cantly improve the quality of experience (QoE) of users and of oad local traf c from the base station. In Chapter 5, we combine LTE-unlicensed with D2D communications. We utilise LTE-unlicensed to enable the operation of D2D in unlicensed bands. We show that not only can this improve the throughput of D2D communications, but also allow D2D to work in the cell central area, which normally regarded as a “forbidden area” for D2D in existing works. We achieve these results mainly through numerical optimisation and simulations. We utilise a wide range of numerical optimisation theories in our works. Instead of utilising the general numerical optimisation algorithms to solve the optimisation problems, we modify them to be suitable for the speci c problems, thereby reducing the computational complexity. Finally, we evaluate our proposed algorithms and systems through sophisticated numer- ical simulations. We have developed a complete system-level simulation framework for D2D communications and we open-source it in Github: https://github.com/mathwuyue/py- wireless-sys-sim

Joint Spectrum and Power Allocation for D2D Communications Underlaying Cellular Networks

This paper addresses the joint spectrum sharing and power allocation problem for device-to-device (D2D) communications underlaying a cellular network (CN). In the context of orthogonal frequency-division multiple-access systems, with the uplink resources shared with D2D links, both centralized and decentralized methods are proposed. Assuming global channel state information (CSI), the resource allocation problem is first formulated as a nonconvex optimization problem, which is solved using convex approximation techniques. We prove that the approximation method converges to a suboptimal solution and is often very close to the global optimal solution. On the other hand, by exploiting the decentralized network structure with only local CSI at each node, the Stackelberg game model is then adopted to devise a distributed resource allocation scheme. In this game-theoretic model, the base station (BS), which is modeled as the leader, coordinates the interference from the D2D transmission to the cellular users (CUs) by pricing the interference. Subsequently, the D2D pairs, as followers, compete for the spectrum in a noncooperative fashion. Sufficient conditions for the existence of the Nash equilibrium (NE) and the uniqueness of the solution are presented, and an iterative algorithm is proposed to solve the problem. In addition, the signaling overhead is compared between the centralized and decentralized schemes. Finally, numerical results are presented to verify the proposed schemes. It is shown that the distributed scheme is effective for the resource allocation and could protect the CUs with limited signaling overhead

Joint Optimization of Signal Design and Resource Allocation in Wireless D2D Edge Computing

In this paper, we study the distributed computational capabilities of device-to-device (D2D) networks. A key characteristic of D2D networks is that their topologies are reconfigurable to cope with network demands. For distributed computing, resource management is challenging due to limited network and communication resources, leading to inter-channel interference. To overcome this, recent research has addressed the problems of wireless scheduling, subchannel allocation, power allocation, and multiple-input multiple-output (MIMO) signal design, but has not considered them jointly. In this paper, unlike previous mobile edge computing (MEC) approaches, we propose a joint optimization of wireless MIMO signal design and network resource allocation to maximize energy efficiency. Given that the resulting problem is a non-convex mixed integer program (MIP) which is prohibitive to solve at scale, we decompose its solution into two parts: (i) a resource allocation subproblem, which optimizes the link selection and subchannel allocations, and (ii) MIMO signal design subproblem, which optimizes the transmit beamformer, transmit power, and receive combiner. Simulation results using wireless edge topologies show that our method yields substantial improvements in energy efficiency compared with cases of no offloading and partially optimized methods and that the efficiency scales well with the size of the network.Comment: 10 pages, 7 figures, Accepted by INFOCOM 202

Resource Allocation Management of D2D Communications in Cellular Networks

To improve the system capacity, spectral performance, and energy efficiency, stringent requirements for increasing reliability, and decreasing delays have been intended for next-generation wireless networks. Device-to-device (D2D) communication is a promising technique in the fifth-generation (5G) wireless communications to enhance spectral efficiency, reduce latency and energy efficiency. In D2D communication, two wireless devices in close proximity can communicate with each other directly without pass through the Base Station (BS) or Core Network (CN). In this proposal, we identify compromises and challenges of integrating D2D communications into cellular networks and propose potential solutions. To maximize gains from such integration, resource management, and interference avoidance are key factors. Thus, it is important to properly allocate resources to guarantee reliability, data rate, and increase the capacity in cellular networks. In this thesis, we address the problem of resource allocation in D2D communication underlaying cellular networks. We provide a detailed review of the resource allocation problem of D2D communications. My Ph.D research will tackle several issues in order to alleviate the interference caused by a D2D user-equipment (DUE) and cellular-userequipment (CUE) in uplink multi-cell networks, the intra-cell and inter-cell interference are considered in this work to improve performance for D2D communication underlaying cellular networks. The thesis consists of four main results. First, the preliminary research proposes a resource allocation scheme to formulate the resource allocation problem through optimization of the utility function, which eventually reflects the system performance concerning network throughput. The formulated optimization problem of maximizing network throughput while guaranteeing predefined service levels to cellular users is non-convex and hence intractable. Thus, the original problem is broken down into two stages. The first stage is the admission control of D2D users while the second one is the power control for each admissible D2D pair and its reuse partner. Second, we proposed a spectrum allocation framework based on Reinforcement Learning (RL) for joint mode selection, channel assignment, and power control in D2D communication. The objective is to maximize the overall throughput of the network while ensuring the quality of transmission and guaranteeing low latency requirements of D2D communications. The proposed algorithm uses reinforcement learning (RL) based on Markov Decision Process (MDP) with a proposed new reward function to learn the policy by interacting with the D2D environment. An Actor-Critic Reinforcement Learning (AC-RL) approach is then used to solve the resource management problem. The simulation results show that our learning method performs well, can greatly improve the sum rate of D2D links, and converges quickly, compared with the algorithms in the literature. Third, a joint channel assignment, power allocation and resource allocation algorithm is proposed. The algorithm designed to allow multiple DUEs to reuse the same CUE channel for D2D communications underlaying multi-cell cellular networks with the consideration of the inter-cell and intra-cell interferences. Obviously, under satisfying the QoS requirements of both DUEs and CUEs, the more the number of the allowed accessing DUEs on a single CUE channel is, the higher the spectrum efficiency is, and the higher the network throughput can be achieved. Meanwhile, implementing resource allocation strategies at D2D communications allows to effectively mitigate the interference caused by the D2D communications at both cellular and D2D users. In this part, the formulated optimization problem of maximizing network throughput while guaranteeing predefined service levels to cellular users. Therefore, we propose an algorithm that solves this nonlinear mixed-integer problem in three steps wherein the first step, subchannel assignment is carried out, the second one is the power allocation, while the third step of the proposed algorithm is the resource allocation for multiple D2D pairs based on genetic algorithm. The simulation results verify the effectiveness of our proposed algorithm. Fourth, integrating D2D communications and Femtocells in Heterogeneous Networks (HetNets) is a promising technology for future cellular networks. Which have attracted a lot of attention since it can significantly improve the capacity, energy efficiency and spectral performance of next-generation wireless networks (5G). D2D communication and femtocell are introduced as underlays to the cellular systems by reusing the cellular channels to maximize the overall throughput in the network. In this part, the problem is formulated to maximize the network throughput under the QoS constraints for CUEs, DUEs and FUEs. This problem is a mixed-integer non-linear problem that is difficult to be solved directly. To solve this problem, we propose a joint channel selection, power control, and resource allocation scheme to maximize the sum rate of the cellular network system. The simulation results show that the proposed scheme can effectively reduce the computational complexity and improve the overall system throughput compared with existing well-known methods