RESOURCE ALLOCATION FOR DEVICE-TO-DEVICE COMMUNICATION IN CELLULAR NETWORKS

Abstract

The massive demand for high data rate applications and enormous use of smart devices is contributing to heavy data traffic in the wireless communication domain. Handling the considerable number of users, high data rate requirements, and heterogeneous applications require modifications in the existing cellular communication. Integration of device-to-device (D2D) communication into the existing cellular system can fulfill these expectations and im prove the system performances such as system throughput, traffic offloading, spectrum, and energy efficiency. Unlike traditional two-hop uplink/downlink transmission via a base station (BS), D2D communication allows a direct transmission to the users in close proximity. This thesis mainly focuses on the underlay D2D communication where D2D users can transmit their data on the channels shared from the existing cellular users (CUs). The in tegration of D2D communication in cellular networks brought some challenges which are addressed in this thesis. We validate the potential of D2D technology in the context of spec tral efficiency employing proper resource management schemes. Our main contributions lie in the intelligent channel selection and power control to maximize the system throughput. First, we study the impact of D2D integration in the cellular system on spectral efficiency. We formulate the joint optimization problem of channel and power allocation for underlay D2Dnetworks that is mixed integer non-linear programming (MINLP) in nature. Each D2D pair is allowed to share multiple uplink channels from different CUs, and each CU is re stricted to share its channel with at most one D2D pair. Our objective is to maximize the total sum rate of D2D users while the performance of shared CU is protected. We provide connectivity to each D2D pair by assigning some channels to each D2D pair. Furthermore, we extend the work to the case where the maximum number of channels to a D2D pair is upper bounded to perform a fair allocation. We analyze the impact of power constraint on individual D2D transmitter as well as on all D2D transmitters. Second, we investigate a more complicated scenario for downlink D2D to serve a large number of D2D users with few channels. We propose a cluster oriented channel assign ment and difference of two convex functions (d.c.) programming based power optimization algorithm for the downlink D2D communication underlaying cellular networks. The ob jective is to maximize D2D throughput while protecting the performance of existing CUs whose channel is reused among multiple D2D pairs, by imposing a minimum rate require ment constraint on each CU. A three stage solution is proposed to solve the MINLP problem: cluster formation to minimize the interference among the D2D pairs followed by an optimal channel assignment using the Hungarian algorithm and then an iterative power optimization algorithm based on d.c. programming. The third part of the thesis proposes a semi-distributed resource allocation to maximize the D2D sum rate by channel assignment and power control. A centralized channel assign ment scheme is proposed based on a well known Gale-Shapley algorithm, and then power control is applied in a distributed manner. The effect of all kind of interferences are taken into consideration during the power control. The main advantage of the proposed subopti mal scheme is a significant reduction in the computational complexity as compared to the state-of-the-art centralized schemes. There is a trade-off between signaling overhead and throughput performance. The last part of the thesis proposes an energy efficient channel and power allocation scheme for joint uplink-downlink D2D users with many-to-one pairing. An iterative algo rithm using Dinkelbach’s method is designed for channel and power allocation to maximize the energy efficiency of D2D users while assuring the quality of service (QoS) of CUs.