Resources Allocation in Underlay Device-to-Device Communications Networks: A Reduced-Constraints Approach

Abstract

Device-to-Device (D2D) communications underlaying cellular networks have emerged as a necessity for a substantial increase in the system throughput and the number of active devices for the future cellular networks. In underlay D2D networks, it is conventional to use different interference management (IM) techniques to allow D2D transmitters to reuse the cellular users' subcarriers. Conventionally, those IM techniques pair a specific number (one or more) of D2D transmitters to each subcarrier and/or allow each D2D transmitter to transmit on a specific number of subcarriers simultaneously in order to achieve the target rates. Due to the mixed-integer nature of those IM techniques, convex optimization techniques can not be used, and usually complex heuristic or game-theoretic approaches are exploited. In this paper, we introduce a reduced-constraints approach to seek sub-optimal joint power allocation and channel assignment solutions for two non-convex, mixed-integer, and non-linear programs (MINLP). Specifically, via the reduced-constraints approach and variable transformation techniques, we can exploit primal-dual algorithms to solve system power minimization and energy-efficiency maximization problems. Extensive numerical simulation results show that the proposed approach outperforms state-of-the-art techniques.

An Optimal Balanced Energy Harvesting Algorithm for Maximizing Two-Way Relaying D2D Communication Data Rate

“…Device-to-device (D2D) communication is one of the most essential technologies in the 5G networks [1], [2]. It allows two nearby devices to directly communicate without the intervention from the base-station (BS) [3]. This direct communication underlaying conventional cellular network not only improves the network spectral efficiency (SE) but also its energy efficiency (EE) [4]- [6].…”

Energy optimized resource and power allocation in an uplink‐based underlay device‐to‐device communication for 5G network

“…Many conventional algorithms were proposed in previous studies 6–30 which explored about resource and power allocation techniques for the DUEs. In Kim and Dong, 6 Iterative Hungarian method was used for the resource allocation of the D2D users and throughput of the system was analyzed.…”

“…In Ningombam and Shin, 23 sectorization‐based resource and power allocation in D2D network was proposed to mitigate the interference so that system performance was improved. To maximize the energy efficiency of the system, a reduced constraints approach‐based Lagrangian method was proposed to allocate the resources in D2D network 24 . In Gao et al, 25 sequential geometric programing method was proposed to allocate the resource and control the power of the D2D users which increased the energy efficiency of the network.…”

“…To maximize the energy efficiency of the system, a reduced constraints approach-based Lagrangian method was proposed to allocate the resources in D2D network. 24 In Gao et al, 25 sequential geometric programing method was proposed to allocate the resource and control the power of the D2D users which increased the energy efficiency of the network. Fractional programming method was used to control the power of D2D users and increased the energy efficiency of the system.…”

Energy Efficient Underlaid D2D Communication for 5G Applications

“…Due to higher spectral efficiency, underlaid is considered superior to overlaid. The different topologies of underlaid communication by using the same frequency channels as cellular and D2D users is explained in [21][22][23]. The improved data rate, efficient bandwidth use, power control, and energy-efficient methods are used [24][25][26][27][28][29][30].…”