Resource Allocation for Energy Harvesting-Aided Device-to-Device Communications: A Matching Game Approach

Abstract

In this paper, we propose an optimization problem of joint spectrum resource matching, power allocation and transmission time duration in energy harvesting (EH) aided device-to-device (D2D) communications underlying cellular network. Particularly, to increase the spectral efficiency (SE), multiple D2D links are permitted to multiplex the same resource block (RB) of cellular user (CU), and multiple cellular RBs are allowed to be reused by one D2D link. Taking into account the Quality of Service (QoS) of cellular users and the harvested energy of D2D links, our objective is to maximize the sum SE of D2D communications. Specifically, the joint problem is a mixed-integer nonlinear programming problem, which has been proved to be NP-hard. In view of this observation, a novel match-based resource allocation algorithm is designed, which contains two key sub-methods with a progressive relationship. First, a manyto-many matching game with externalities is developed, which produces spectrum reusing during each iteration. Second, on the basis of the spectrum matching, a resource allocation algorithm is presented by employing the Lagrange multiplier and Bisection search method. Finally, comprehensive simulation results are provided to demonstrate the performance of the proposed algorithm with different network parameter settings. Numerical results validate that the proposed algorithm can achieve near-optimal performance and significantly outperform the other matching strategies in aspects of SE.

Unsupervised Learning for Resource Allocation and User Scheduling in Wideband MU-MIMO Systems

“…In [21]- [23], user scheduling problems are formulated as many-to-one or many-to-many matching games. Since CCI exists among users in the same RSGs, an ideal algorithm should decide not only which RB the users are matched with, but also which users are matched in the same RB, and thus externality exists.…”

A matching‐based context‐aware relay assignment scheme with power control in ad‐hoc wireless networks

“…To decrease the complexity of computational, most of the works assume a subset of the joint optimization problems [7][8][9][10][11]. Because the relay selection and channel assignment are naturally combinatorial, matching-based approaches are adopted in some articles [12][13][14][15]. The problems solved by the matching-based algorithms are mostly divided into three categories: one-to-one matching, many-to-one (known as college admission) matching, and many-to-many matching.…”

Resource Allocation Algorithm for NOMA-Enhanced D2D Communications with Energy Harvesting

“…In [14][15][16][17], the D2D users harvest energy from the surrounding environments. Authors in [14] utilize the Paretooptimal boundary and a subcarrier allocation method to allocate power and channel for D2D users under the energy causality constraint and battery overflow constraint.…”

“…Authors in [14] utilize the Paretooptimal boundary and a subcarrier allocation method to allocate power and channel for D2D users under the energy causality constraint and battery overflow constraint. Manyto-many matching problem between cellular users and D2D users is investigated in [15], and the transmission power of D2D users and transmission time are optimized under the energy harvesting constraint. In [16], authors propose a lowcomplexity energy-aware space matching method to solve the channel and power allocation problems.…”

“…In [17], an iterative algorithm based on Dinkelbach and Lagrangian constraint optimization is proposed to maximize the average energy efficiency of D2D users. However, authors [14][15][16][17] assume that the full system information is available before the transmission process and propose the offline algorithm. Actually, there is no prior knowledge about the harvested energy and the system information.…”