Joint Power and Channel Allocation for Underlay D2D Communications with Proportional Fairness

Since D2D (Device-to-Device) communication was proposed in cellular network as a new paradigm for enhancing network performance, many works have been done on resource allocation to improve system throughput and energy efficiency (EE) for underlay D2D communications. However, the system long-term average fairness as one of the system main performance metrics was rarely considered especially when users are moving. In this paper, we formulate the joint power and channel allocation problem aiming at maximizing the system fairness subject to the minimum required SINRs (Signal to Interference and Noise Ratios) and power consumption limits of cellular and active D2D links. To solve the above problem practically, we first decompose our original problem into two sub-problems (power and channel allocation), then solve them sequentially. Simulation results show that our proposed algorithm can dramatically enhance the system fairness and slightly improve the system throughput comparing with existing method

Resource Allocation for D2D Underlay Communications With Proportional Fairness Using Iterative-Based Approach

In this paper, we develop a novel resource allocation scheme that aims to improve the system fairness, with minimum SINR (Signal to Interference and Noise Ratio) constraints and power limits for the Device-to-Device (D2D) underlay communications. Since the evaluation of the system fairness is different for t=1 and t≥2 , where t is the scheduling period, we divide our joint optimization problem into two cases: t=1 and t≥2 . For each case, we decompose the joint optimization problem into two sub-problems: power and channel allocations. We then propose the corresponding power allocation algorithm for each case. By introducing virtual D2D links, we model the channel allocation as a 3-D (3-Dimensional) assignment problem, which is effectively solved by our proposed 2-D (2-Dimensional) iterative method. Simulation results show that our proposed iterative method can produce the close-to-optimal performance with low computational complexity. Moreover, comparing with existing schemes, our proposed scheme can not only enhance the system fairness but also improve the overall throughput

Energy-Efficient Resource Allocation for Device-to-Device Underlay Communication

Device-to-device (D2D) communication underlaying cellular networks is expected to bring significant benefits for utilizing resources, improving user throughput and extending battery life of user equipments. However, the allocation of radio and power resources to D2D communication needs elaborate coordination, as D2D communication can cause interference to cellular communication. In this paper, we study joint channel and power allocation to improve the energy efficiency of user equipments. To solve the problem efficiently, we introduce an iterative combinatorial auction algorithm, where the D2D users are considered as bidders that compete for channel resources, and the cellular network is treated as the auctioneer. We also analyze important properties of D2D underlay communication, and present numerical simulations to verify the proposed algorithm.Comment: IEEE Transactions on Wireless Communication

Review on Radio Resource Allocation Optimization in LTE/LTE-Advanced using Game Theory

Recently, there has been a growing trend toward ap-plying game theory (GT) to various engineering fields in order to solve optimization problems with different competing entities/con-tributors/players. Researches in the fourth generation (4G) wireless network field also exploited this advanced theory to overcome long term evolution (LTE) challenges such as resource allocation, which is one of the most important research topics. In fact, an efficient de-sign of resource allocation schemes is the key to higher performance. However, the standard does not specify the optimization approach to execute the radio resource management and therefore it was left open for studies. This paper presents a survey of the existing game theory based solution for 4G-LTE radio resource allocation problem and its optimization