Power Adaptation in Buffer-Aided Full-Duplex Relay Networks With Statistical CSI

Abstract

In networks with multiple wireless nodes and especially in fast changing environments, the continuous acquisition of Channel State Information (CSI) may become infeasible. In this paper, we study the relay selection problem for a cooperative network, where Full-Duplex (FD) relays are equipped with buffers and only statistical CSI is available at the transmitters (CSIT). For this setting, a novel relay selection algorithm is proposed, named HyQoS, relying only on statistical CSIT and performing power adaptation. HyQoS solves an optimization problem for selecting the optimal set of relays. We consider two optimization approaches: 1) minimization of the total power consumed in the network, and 2) maximization of the throughput per energy unit, while guaranteeing a specific Quality of Service (QoS), in terms of Successful Transmission Probability (STP). The power allocation problem is formulated as a nonlinear optimization one, taking into account inter-relay interference and residual loop interference. Numerical results show that HyQoS can reduce the power expenditure and increase the throughput, by using only statistical CSIT.

LoLa4SOR: Leveraging Successive Transmissions for Low-Latency Buffer-Aided Opportunistic Relay Networks

“…However, when IC cannot be performed, R rx tries to directly decode the desired signal by examining if the SINR SRrx is above the capture ratio γ 0 , thus treating the IRI as noise. In this case, the successful transmission probability will be given by [39]:…”

Survey on half‐ and full‐duplex relay based cooperative communications and its potential challenges and open issues using Markov chains

“…By increasing demand for data rate, the power consumption in the network is more interesting for FDR. In [84], Nomikos et al have presented buffer‐aided relay cluster networks (BRCNs) to achieve high TP by minimising the overall power consumption of the network at each frame.…”

Joint Trajectory and Communication Design for Buffer-Aided Multi-UAV Relaying Networks

“…Inequations (1)-(3) are constraints on the UAV's mobility, including the UAV's initial and final location, the maximum speed of UAV and collision avoidance. Inequations (6)- (8) are relay selection constraints, and Inequations (9) and (10) are the average power and peak power constraints of transmit power. Since all UAVs can only transmit the data that have been previously stored from S, according to the Shannon formula, Problem (17) can be rewritten as:…”

“…We note that Problem (19) is still non-convex because the constraints in (6)- (8) involve integer constraints and the information causality constraint in (18b) is non-convex. To solve the integer constraints, we relax the binary variables in (8) into continuous variables, i.e., 0 ≤ a k,m [n] ≤ 1, m ∈ {S, D} , ∀k, n. Furthermore, the slack variables u k,m [n] are introduced. First, we consider the following problem:…”

“…Studies have shown that the buffer aided relaying technique can effectively solve the adverse effects brought by time varying channels. It enables relays to have the ability of data storage, breaks through the traditional transmission mode, and flexibly uses the best channel [7,8]. Therefore, in this paper, it is considered that all UAV relays are equipped with a buffer and employed in delay tolerant applications [4].…”