Optimal Resource Allocation in Multicast Device-to-Device Communications Underlaying LTE Networks

TL;DR

This paper develops a flexible resource allocation framework for multicast D2D communications under LTE, optimizing throughput while managing interference through novel algorithms and solving a complex MINLP problem.

Contribution

It introduces a new formulation and solution methods for resource sharing in multicast D2D under LTE, including a GBD-based optimal approach, a greedy algorithm, and a heuristic.

Findings

Greedy algorithm achieves near-optimal performance.

Heuristic algorithm offers good performance with lower complexity.

Proposed methods effectively manage interference and improve throughput.

Abstract

In this paper, we present a framework for resource allocations for multicast device-to-device (D2D) communications underlaying a cellular network. The objective is to maximize the sum throughput of active cellular users (CUs) and feasible D2D groups in a cell, while meeting a certain signal-to-interferenceplus- noise ratio (SINR) constraint for both the CUs and D2D groups. We formulate the problem of power and channel allocation as a mixed integer nonlinear programming (MINLP) problem where one D2D group can reuse the channels of multiple CUs and the channel of each CU can be reused by multiple D2D groups. Distinct from existing approaches in the literature, our formulation and solution methods provide an effective and flexible means to utilize radio resources in cellular networks and share them with multicast groups without causing harmful interference to each other. A variant of the generalized bender decomposition (GBD) is applied to optimally solve the MINLP problem. A greedy algorithm and a low-complexity heuristic solution are then devised. The performance of all schemes is evaluated through extensive simulations. Numerical results demonstrate that the proposed greedy algorithm can achieve closeto- optimal performance, and the heuristic algorithm provides good performance, though inferior than that of the greedy, with much lower complexity.