Adaptive Relay Selection and Power Allocation for OFDM Cooperative Underwater Acoustic Systems - 2018

PROJECT TITLE :

Adaptive Relay Selection and Power Allocation for OFDM Cooperative Underwater Acoustic Systems - 2018

ABSTRACT:

The increasing use of relays in underwater acoustic (UWA) Communications is a driving force to explore efficient techniques that can significantly improve the system performance. To fully exploit the advantages of cooperative systems, efficient management of resources including relays and power is required. During this Project, both optimal relay selection and power loading issues are investigated for an orthogonal frequency division multiplexing (OFDM) cooperative transmission over UWA channel. In our analysis, we tend to think about amplify-and-forward (AF) relaying with perfect channel state information (CSI) at the source, relay, and destination nodes. Moreover, we assume sparse and frequency-selective Rician fading within the presence of colored Gaussian ambient noise. Unlike previous works on this subject, in our study, the ability of noise isn't identical for all subcarriers at each the relay and destination nodes. We tend to solve 2 optimization problems that depend on the minimization of the bit error rate (BER) and maximization of the system capability. In each drawback, each optimal relay selection and power loading issues are addressed in 2 dependent phases. In the primary section, an unconstrained optimization problem is solved to see the optimal relay out of multiple relays vertically located at different depths of water. We adopt all-subcarrier (AS) basis approach in our OFDM-based transmission model in that a single relay is engaged to transmit the complete OFDM block to the destination. In the second phase, after selecting the optimal relay, another optimization problem is solved to get the optimal power allocation. This is jointly done at each the source and relay nodes beneath total power constraint and mounted subcarrier rate. Intensive simulations are conducted to evaluate the performance of proposed algorithms underneath totally different situations.

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