Abstract
In this paper, we investigate the relay placement and power allocation for decode-and-forward (DF) cooperative relaying over correlated lognormal shadowed Rayleigh fading channels. Assuming that maximum-ratio combining is performed at the destination, we first derive an upper bound of symbol error rate (SER) with M-phase-shift keying (PSK) modulation. Then, three optimization problems are formulated to minimize the obtained SER upper bound, namely optimal relay placement with fixed power allocation, optimal power allocation with fixed relay location, and joint optimization of relay placement and power allocation. It is shown by the analytical results that the correlation coefficients and the standard deviations of shadowing have significant impacts on the optimal relay placement and power allocation. The simulation results validate our analysis and show that the SER upper bound is asymptotically tight in the high signal-to-noise ratio (SNR) regime.
Highlights
The concept of cooperative relaying has been adopted in next-generation mobile communication standards, such as WiMAX and LTE-Advanced [1,2]
The simulation results show that joint optimization obtains the best symbol error rate (SER) performance and the SER upper bound is asymptotically tight in the high signal-to-noise ratio (SNR) regime
The gap between the simulation results and the SER upper bound gets smaller with the increase of SNR, which means that the SER upper bound is asymptotically tight in the high SNR regime
Summary
The concept of cooperative relaying has been adopted in next-generation mobile communication standards, such as WiMAX and LTE-Advanced [1,2]. We derive an upper bound of symbol error rate (SER) for DF cooperative relaying over correlated. Lognormal shadowed Rayleigh fading channels with Mphase-shift keying (PSK) modulation, which shows how the correlation coefficients and the standard deviations of shadowing impact the SER performance. By minimizing the obtained SER upper bound, we formulate and compare three schemes to optimize the relay placement and power allocation. The SER upper bound can be obtained by averaging (9) over the correlated shadowing, i.e., Pe ≤ Eξsr,ξsd,ξrd. By substituting (13) into (11), the SER upper bound considering the effects of path loss, correlated shadowing and flat Rayleigh fading, is given as. From (14), we can see that the SER upper bound is determined by the distances between these nodes and the correlation coefficients and standard deviations of shadowing
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