Cloud Compute-and-Forward With Relay Cooperation

Abstract

Abstract-We study a cloud network with M distributed receiving antennas and L users, which transmit their messages towards a centralized decoder (CD), where M ≥ L. We consider that the cloud network applies the Compute-and-Forward (C&F) protocol, where L antennas/relays are selected to decode integer equations of the transmitted messages. In this work, we focus on the best relay selection and the optimization of the Physical-Layer Network Coding (PNC) at the relays, aiming at the throughput maximization of the network. Existing literature optimizes PNC with respect to the maximization of the minimum rate among users. The proposed strategy maximizes the sum rate of the users allowing non-symmetric rates, while the optimal solution is explored with the aid of the Pareto frontier. The problem of relay selection is matched to a coalition formation game, where the relays and the CD cooperate to maximize their profit. Efficient coalition formation algorithms are proposed, which perform joint relay selection and PNC optimization. Simulation results show that a considerable improvement is achieved compared to existing results, both in terms of the network sum rate and the players' profits.Index Terms-Cloud radio access networks, cloud base stations, compute-and-forward, physical layer network coding, relay selection, cooperative game theory.

A comprehensive survey on resource allocation for CRAN in 5G and beyond networks

“…Also, RRHs relay information to the cloud decoder for further processing which gives rise to the issues related to distributed compression and decoding specifically in multiantenna systems. Problems related to the CRAN uplink have been vastly investigated in literature including [44]- [46], [52], [56]- [58], [61], [65], [68], [69], [71]- [73], [75], [84], [89], [90]. The downlink design in a CRAN is also important as the RRHs transmit the received signals from the BBUs to users.…”

“…Like any other optimization problems, optimization problems in a CRAN can be single objective addressing issues such as energy minimization, capacity maximization, etc. Many single objective optimization problems have been considered in literature [44]- [52], [54], [55], [57], [67]- [75], [77]- [79], [81]- [86], [88], [89]. Similarly, optimization problems can be multi-objective which can address multiple conflicting or nonconflicting objectives simultaneously.…”

Energy‐Efficient Incentives Resource Allocation Scheme in Cooperative Communication System

“…Initialize the intelligent water drops' parameters and the soil quantity on the path according to (9).…”

Performance of non‐orthogonal multiple access: analysis using compute‐and‐forward cooperative relaying in 5G networks

“…In the CF strategy, the received signal is compressed and forwarded to the destination(s) [19]. The major drawback of both the AF and CF strategies is noise accumulation, especially in a multi‐hop network [20, 21].…”