Abstract
The exact expressions and simple tight lower bounds for end-to-end average symbol error rate (ASER) and outage probability (OP) are derived in amplify-and-forward (AF) source-relay-destination cooperative link, provided that source-destination path is correlated with the source-relay path. Afterward, an optimum power allocation (PA) and relay location (RL) algorithm is presented. The effect of correlation factor and path-loss exponent (PLE) on the optimal nodes’ power and location is investigated. The results show that optimizing relay location is more efficient than power allocation. Furthermore, a machine learning (ML) implementation of the proposed convex optimization-based algorithm is investigated to cop the computational burden. Specifically, the data set is obtained by using the proposed algorithm. Given the data set, the optimization algorithm can be translated into a regression problem, and feed-forward neural networks (FNNs) are then employed to solve this problem efficiently. The simulation results represented a compromise between accuracy and computation times for the ML-based joint PA-RL optimization.
Highlights
Towards the Fifth Generation (5G) networks, the concept of moving networks has emerged where both devices and cells are in constant or temporary motion [1]
In [8], we have considered the optimization of power allocation and relay location in a Cooperative Relays Systems (CRSs) in the Rayleigh channel with free space path loss
In [10], we looked at the optimization of CRS in the Nakagami-m channel, but in [10] all the inter-nodes links were assumed to be independent and identically distributed Nakagami-m fading channels
Summary
Towards the Fifth Generation (5G) networks, the concept of moving networks has emerged where both devices and cells are in constant or temporary motion [1]. The average symbol error rate (ASER) over correlated Nakagami-m fading channel, has received little attention In this context, [7] examined the performance of a Decode-and-Forward (DF) system by using the space-time orthogonality principle through Nakagami-m channels with integer m. In practice, a correlation exists between the source–relay and source-destination channels, e.g., for nomadic relay cooperation in the downlink of a cellular network in 5G. B. SIGNAL MODEL Fig. presents CRS principles for downlink in a cellular network, with a single AF cooperative Nomadic relay. SIGNAL MODEL Fig. presents CRS principles for downlink in a cellular network, with a single AF cooperative Nomadic relay This scheme consists of a macro base station (BS), a mobile station (MS) with a single antenna, and an NRN deployed to achieve the transmit spatial diversity for link-quality improvement. R-D and S-R links, respectively; Ps and Pr are the transmitted signal power of the source and the relay, respectively; N0 is the noise received power; hs,d , hs,r , and hr,d are the fading channel gains of the S-D, S-R, and R-D links, respectively
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