Open AccessDistributed differential beamforming and power allocation for cooperative communication networks
Author(s) -
Samer Alabed,
Issam Maaz,
Mohammad Al-Rabayah
Publication year - 2020
Publication title -
international journal of power electronics and drive systems/international journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
eISSN - 2722-2578
pISSN - 2722-256X
DOI - 10.11591/ijece.v10i6.pp5923-5931
Subject(s) - computer science , channel state information , decoding methods , transmitter , beamforming , relay , bit error rate , overhead (engineering) , cooperative diversity , low latency (capital markets) , coding (social sciences) , latency (audio) , antenna diversity , wireless , space–time code , computer network , real time computing , computer engineering , channel (broadcasting) , telecommunications , power (physics) , mimo , fading , mathematics , physics , statistics , quantum mechanics , operating system
Many coherent cooperative diversity techniques for wireless relay networks have recently been suggested to improve the overall system performance in terms of the achievable data rate or bit error rate (BER) with low decoding complexity and delay. However, these techniques require channel state information (CSI) at the transmitter side, at the receiver side, or at both sides. Therefore, due to the overhead associated with estimating CSI, distributed differential space-time coding techniques have been suggested to overcome this overhead by detecting the information symbols without requiring any (CSI) at any transmitting or receiving antenna. However, the latter techniques suffer from low performance in terms of BER as well as high latency and decoding complexity. In this paper, a distributed differential beamforming technique with power allocation is proposed to overcome all drawbacks associated with the later techniques without needing CSI at any antenna and to be used for cooperative communication networks. We prove through our analytical and simulation results that the proposed technique outperforms the state-of-the-art techniques in terms of BER with comparably low decoding complexity and latency.