Distributed interference-aware energy-efficient resource allocation for device-to-device communications underlaying cellular networks

Abstract

Abstract-The introduction of device-to-device (D2D) into cellular networks poses many new challenges in the resource allocation design due to the co-channel interference caused by spectrum reuse and limited battery life of user equipments (UEs). In this paper, we propose a distributed interference-aware energy-efficient resource allocation algorithm to maximize each UE's energy efficiency (EE) subject to its specific quality of service (QoS) and maximum transmission power constraints. We model the resource allocation problem as a noncooperative game, in which each player is self-interested and wants to maximize its own EE. The formulated EE maximization problem is a nonconvex problem and is transformed into a convex optimization problem by exploiting the properties of the nonlinear fractional programming. An iterative optimization algorithm is proposed and verified through computer simulations.

Multiple resource allocation in device‐to‐device communication underlaying cellular networks from an end‐to‐end energy‐efficient perspective

“…|g k, j n * , m * | 2 q peak + |g i * , j n * , m * | 2 p peak (12) From (11) and (12), we can find that although the transmission power has been temporarily set as p peak and q peak , the multiuser interference is still very complex, for it changes with channel gains and the results of RU allocation. To handle the multiuser interference, we introduce two interference constraints I C and I D which are the maximum multiuser interference temperature on each RU [34] for CUEs and DUEs, respectively.…”

Mode Switching for Energy-Efficient Device-to-Device Communications in Cellular Networks

“…Theorem 2: The objective function in (13) is strictly monotonically increase on the generated sequence {V…”

“…The main idea of CCCP is to iteratively linearise the convex part of the D.C. objective function by the first order Taylor expansion around the current point. Thus, (13) can be solved by the following sequential convex programming (14) is a convex optimization problem and thus can be solved efficiently by the interior point method. The above CCCP can be summarized as in Table III.…”

“…In particular, an auction-based resource allocation algorithm has been proposed in [12] to maximize the battery life of D2D terminals while in [13] a non-cooperative game based method has been designed to maximize each user's EE for both D2D pairs and RCUs. In [14], a reverse iterative combinatorial auction based method has been proposed to improve network throughput and reduce the transmit power consumption of user terminals for D2D downlink resource sharing while in [15], coalition game based method has been presented to maximize the system EE for D2D uplink resource sharing.…”

Resource and energy efficient device to device communications in downlink cellular system

“…In [2], energy efficient power allocation schemes in three different resource sharing modes were discussed under the maximum transmission power constraint. Using a noncooperative game theory, a distributed interferenceaware energy efficient resource allocation algorithm to maximize each user's EE subject to both transmission power and rate constraints is proposed in [3]. To maximize the EE of D2D communications, a joint resource allocation and power control scheme has been studied in [4].…”