Distributed differential beamforming and power allocation for cooperative communication networks

Abstract

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.

Proposed different relay selection schemes for improving the performance of cooperative wireless networks

“…Many schemes [26], [27] of cooperation can be divided into three famous approaches or systems such as amplify and forward (AF) relay as shown in Figure 1 (a), decode and forward (DF) relay as shown in Figure 1 (b) and compress and forward (CF) relay as shown in Figure 1 (c), the CF relaying schemes are noticed to the cases which the relays forward quantized, compressed or estimated versions of its observation to the destination [28]- [30].…”

A low complexity distributed differential scheme based on orthogonal space time block coding for decode-and-forward wireless relay networks

“…Advances made in MIMO signal processing techniques have shown tremendous improvements in reliability and throughput [13]- [19]. However due to size, cost, and hardware constraints, the use of MIMO techniques in ad-hoc networks may not always be feasible especially in small devices.…”

A computationally efficient non-coherent technique for wireless relay networks

“…Recently, space-diversity techniques that use multiple-input multiple-output (MIMO) systems have been studied extensively [7]- [12]. These systems have attracted a lot of attention since they can be merged with other types of diversity techniques to provide additional coding and diversity gain without expanding the bandwidth or the transmission power [13]- [19]. Furthermore, MIMO techniques have been proposed to improve the channel throughput linearly with the minimum number of transmitting and receiving antennas.…”

“…Currently, many cooperative protocols have been suggested. These are divided into two main categories: the amplify and forward (AF) protocols [1], [13], [20] and the decode and forward (DF) protocols [7], [22]. Cooperative techniques can be categorized into two main classes regarding the availability of the channel state information (CSI).…”