Energy‐efficient power allocation for device‐to‐device communications underlaid cellular networks using stochastic geometry

Abstract

In this paper, we study an energy efficiency maximization problem in uplink for device-to-device (D2D) communications underlaid with cellular networks on multiple bands. Utilizing stochastic geometry, we derive closed-form expressions for the average sum rate, successful transmission probability, and energy efficiency of cellular and D2D users. Then, we formulate an optimization problem to jointly maximize the energy efficiency of D2D and cellular users and obtain optimum transmission power of both D2D and cellular users. In the optimization problem, we guarantee the quality-of-service of users by taking into account the success transmission probability on each link. To solve the problem, first we convert the problem into canonical convex form. Afterwards, we solve the problem in two phases: energy efficiency maximization of devices and energy efficiency maximization of cellular users. In the first phase, we maximize the energy efficiency of D2D users and feed the solution to the second phase where we maximize the energy efficiency of cellular users. Simulation results reveal that significant energy efficiency can be attained, eg, 10% energy efficiency improvement compared to fix transmission power in a high-density scenario.Trans Emerging Tel Tech. 2019;30:e3768.wileyonlinelibrary.com/journal/ett of D2D communications while diminishing the performance degradation of the cellular system due to new sources of interference. In particular, power control is one of the promising approaches that mitigates interference. 5 In the work of Elsawy et al, 6 a power control scheme is proposed to manage the cross-tier interference between cellular and D2D users. Zhang et al 7 proposed an interference-aware algorithm for power control in D2D communications underlaying cellular networks. In the work of Memmi et al, 8 a single-cell D2D underlay cellular network is considered. Centralized and distributed algorithms are proposed to find the users' optimal power transmission. Dynamic power control for a D2D communication underlaying uplink multicell network is investigated in the work of Jiang et al, 9 considering interference mitigation. However, power control is a key technique to manage the interference; both the EE and quality-of-service (QoS) are still influenced by the interference in the network.EE is a metric quantifying the efficiency of resource utilization. In fact, EE not only brings considerable economic benefits into the network but also can be interpreted as concerning about the environment. 10 Extensive research studies have been devoted to the EE of the system. EE maximization in the D2D communication underlaying cellular network in the cloud radio access network is studied by Zhou et al. 1 A closed-form expression for EE is derived in the work of Altman et al 11 by utilizing stochastic geometry tool. In this study, EE is maximized by optimizing the transmit power and density of the BS in cellular networks. An energy-efficient power control algorithm is proposed in the work of Wu et al 12 to share resources among th...

Spectral and Energy Efficient D2D Communication Underlay 5G Networks

“…A lot of research tried to solve this problem either through network coding, mode selection, resource allocation or signal processing [3,10]. Authors in [3] studied resource sharing between cellular and D2D devices underlay cellular network for different modes.…”

“…In [10], the maximum transmission power of a D2D UE was derived from its location compared to eNodeB; consequently a dynamic power based resource allocation scheme was proposed to assign the best cellular link that mitigates interferences. In [11], a joint modulation, resource allocation, and mode selection schema is considered to minimize interferences and guarantee the QoS requirement.…”

“…Focusing on resource allocation schemas, centralized and distributed approaches have been investigated even with or without perfect channel state information (CSI). Many papers focused on analytical approximations, such as stochastic geometry [16], game theory [17], and mixed integer programming [18] to propose a centralized scheduling algorithm that manages all D2D and cellular communications. However these approaches require the knowledge of the CSI of all D2D links' at the eNodeB level.…”

“…All DUEs are competing to allocate the best RBs. Each of them is a rational player and aims to maximize its own payoff given by the equation (10). Any UE knows its coordinates in the cell, and the eNodeB broadcasts the locations and RB allocations of CUEs to D2D in the pair discovery step.…”

“…Let the iteration index. For any given D2D pair and at each iteration, the optimal resource allocation is obtained by solving the equation (10).…”