Delay- and diversity-aware buffer-aided relay selection policies in cooperative networks

Abstract

Buffer-Aided (BA) relaying has shown tremendous performance improvements in terms of throughput and outage probability, although it has been criticized of suffering from long delays that are restrictive for applications, such as video streaming, Web browsing, and file sharing. In this paper, we propose novel relay selection policies aiming at reducing the average delay by incorporating the buffer size of the relays into the decision making of the relay selection process. More specifically, we first propose two new delay-aware policies. One is based on the hybrid relay selection algorithm, where the relay selection takes into account the queue sizes so that the delay is reduced and the diversity is maintained. The other approach is based on the max − link relay selection algorithm. For the max − link algorithm, a delay-aware only approach starves the buffers and increases the outage probability of the system. Thus, for max − link, we propose a delay-and diversity-aware BA relay selection policy targeting the reduction of the average delay, while maintaining the diversity of the transmission. The proposed policies are analyzed by means of Markov Chains and expressions for the outage, throughput, and delay are derived. The asymptotic performance of the policies is also discussed. The improved performance in terms of delays and the use of the proposed algorithms are demonstrated via extensive simulations and comparisons, signifying, at the same time, the need for adaptive mechanisms to handle the interplay between delay and diversity.

Minimum Power Scheduling under Rician Fading in Full-Duplex Relay-Assisted D2D Communication

“…Similarly, DDA-NOMA is characterized by reduced delay with increasing K. Contrary to single user transmissions, NOMA transmission achieves reduced delay as additional relays are added to the network. Finally, both algorithms offer a stable delay performance for high SNR independently of K, as it is shown in [19] for the delay-aware and diversity-aware max − link algorithms.…”

“…When a large number K of relays is available, the diversity gain reaches a value of 2K. Furthermore, a number of works have provided delay-aware versions of HRS see, e.g., [17]) and max − link (see, e.g., [18], [19]) to improve delay performance. Within this context, in [20], through centralized coordination, Buffer State Information (BSI) is exchanged and the best relay is selected, as long as buffers are not empty or full.…”

“…Numerical results show that for a buffer size L ≤ 3 the proposed algorithm offers lower delay than max − link. Finally, in [19] two max − link modifications were provided exploiting BSI. The delay-aware version of max − link achieves low average delay, while diversity is sacrificed, as buffers tend to be empty, thus reducing the number of available relays for selection.…”

“…Moreover, the process for choosing the optimal power allocation coefficient α for NOMA is given in detail, assuming the existence of two users requiring a fixed rate r 0 . Then, two BA ORS algorithms are proposed based on the delay-and diversity-aware algorithms of [19]. The first algorithm, namely Delay-Aware NOMA (DA-NOMA), prioritizes the transmission in the {R→D} link from the relay with the maximum buffer length and if a feasible set of links to the two destinations does not exist, a transmission in the {S→R} link is performed towards the relay with the minimum buffer length.…”

Cloud-Driven Multi-Way Multiple-Antenna Relay Systems: Best-User-Link Selection and Joint Mmse Detection

“…Therefore, we choose the cluster and the relay R i that fulfil (15) to receive M s packets from the selected cluster. For each cluster, in the fourth step, we calculate the metrics A Rij S1 related to the RS 1 links of each matrix H rij,s1 associated with each pair of relays R i and R j , for BC mode:…”