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Several techniques are recently proposed to improve the robustness of wireless communication systems, increase the throughput, and overcome channel impairments such as multi-user interference and multi-path fading. Among them, using multiple-antennas is one of the most remarkable techniques as it allows to improve the error performance and the data rate without an increase in the frequency bandwidth or transmitted power. However, multiple-antenna techniques are not applicable in all ad-hoc networks due to hardware constraints. As an alternative, cooperative diversity techniques have been proposed to achieve gains similar to that of multiple-antenna techniques. In this thesis, we develop computationally efficient multiple-antenna and cooperative diversity techniques for wireless communication networks which offer an improved tradeoff between computational complexity, error performance, and data rate. We first consider space-time block coding for conventional multiple antenna systems. We propose a low complexity decoder for quasi-orthogonal space-time block codes. Both the coherent and non-coherent implementations of this decoder are developed. The proposed decoder can provide a substantially improved tradeoff between the complexity and performance as compared to state-of-the-art decoding techniques. The proposed decoder enjoys a nearly linear decoding complexity and it approximately achieves the optimal performance of the maximum-likelihood decoder.

Recently, cooperative diversity strategies for two-way wireless relay networks have been proposed using the amplify-and-forward and the decode-and-forward protocols. Although the simultaneous bidirectional decode and-forward transmission has been shown to outperform other decode-and-forward strategies, it has mainly two disadvantages: high relay decoding complexity and the impossibility to use the direct link between the communicating terminals. In this thesis, we propose novel coherent and non-coherent simultaneous bidirectional decode-and-forward distributed space-time coding strategies that provide a higher coding gain and enjoy a substantially lower relay decoding complexity than the state-of-the-art strategies at the same symbol rate. In the proposed strategies, the communicating terminals can benefit from the direct link which is not exploited by other existing simultaneous bidirectional transmission strategies. Various differential distributed space-time coding strategies for two-way relay networks using the amplify-and-forward protocol which do not require channel state information either at the relays or at the terminals have been proposed. The simultaneous two-way differential distributed space-time coding strategy using the amplify-and-forward protocol has been shown to outperform the conventional differential four-phase strategy in the low to medium signal-to-noise ratio region. However, there are mainly three disadvantages associated with it: I) the relay power wasted for transmitting redundant information at either side, ii) the direct link between the communicating terminals can not be used and iii) the considerable bias at high signal-to-noise ratio. In this work, amplify-and-forward differential distributed space-time coding strategies for two-way wireless relay networks are developed, that provide a higher coding gain than the state-of-the art strategies. In the proposed strategies, the relays do not waste power to transmit redundant information at either side and the communicating terminals can fully use the direct link between them. Although differential distributed space-time coding strategies do not require channel state information at the relays, they are associated with a low error performance, a high latency, and decoding complexity. Another strategy used in relay networks relies on coherent processing of the relay signals using distributed beamforming techniques. This strategy enjoys a good error performance and low decoding complexity while offering an optimal decoding delay. However, a common requirement in distributed beamforming is the availability of perfect channel state information at all nodes. To avoid this requirement, we introduce a distributed differential beamforming strategy that combines the differential diversity and the distributed beamforming strategy while retaining the benefits of both approaches. The proposed strategy does not require channel state information at any node and enjoys a good error performance, optimal delay, and low decoding complexity.