Modified quasi-orthogonal space-time block coding in distributed wireless networks

Cooperative networks have developed as a useful technique that can achieve the same advantage as multi-input and multi-output (MIMO) wireless systems such as spatial diversity, whilst resolving the difficulties of co-located multiple antennas at individual nodes and avoiding the effect of path-loss and shadowing. Spatial diversity in cooperative networks is known as cooperative diversity, and can enhance system reliability without sacrificing the scarce bandwidth resource or consuming more transmit power. It enables single-antenna terminals in a wireless relay network to share their antennas to form a virtual antenna array on the basis of their distributed locations. However, there remain technical challenges to maximize the benefit of cooperative communications, e.g. data rate, asynchronous transmission and outage. In this thesis, therefore, firstly, a modified distributed quasi-orthogonal space-time block coding (M-D-QO-STBC) scheme with increased code gain distance (CGD) for one-way and two-way amplify-and-forward wireless relay networks is proposed. This modified code is designed from set partitioning a larger codebook formed from two quasi-orthogonal space time block codes with different signal rotations then the subcodes are combined and pruned to arrive at the modified codebook with the desired rate in order to increase the CGD. Moreover, for higher rate codes the code distance is maximized by using a genetic algorithm to search for the optimum rotation matrix. This scheme has very good performance and significant coding gain over existing codes such as the open-loop and closed-loop QO-STBC schemes. In addition, the topic of outage probability analysis in the context of multi-relay selection from $N$ available relay nodes for one-way amplify-and-forward cooperative relay networks is considered together with the best relay selection, the $N^{th}$ relay selection and best four relay selection in two-way amplify-and-forward cooperative relay networks. The relay selection is performed either on the basis of a max-min strategy or one based on maximizing exact end-to-end signal-to-noise ratio. Furthermore, in this thesis, robust schemes for cooperative relays based on the M-D-QO-STBC scheme for both one-way and two-way asynchronous cooperative relay networks are considered to overcome the issue of a synchronism in wireless cooperative relay networks. In particular, an orthogonal frequency division multiplexing (OFDM) data structure is employed with cyclic prefix (CP) insertion at the source in the one-way cooperative relay network and at the two terminal nodes in the two-way cooperative network to combat the effects of time asynchronism. As such, this technique can effectively cope with the effects of timing errors. Finally, outage probability performance of a proposed amplify-and-forward cooperative cognitive relay network is evaluated and the cognitive relays are assumed to exploit an overlay approach. A closed form expression for the outage probability for multi-relay selection cooperation over Rayleigh frequency flat fading channels is derived for perfect and imperfect spectrum acquisitions. Furthermore, the M-QO-STBC scheme is also proposed for use in wireless cognitive relay networks. MATLAB and Maple software based simulations are employed throughout the thesis to support the analytical results and assess the performance of new algorithms and methods

Energy-Efficient Multiple Relay Selection in Cognitive Radio Networks

Cognitive Radios play very important role in military applications due to their capability to adapt intelligently according to the prevailing environmental conditions. Relays form the main communication enablers in infrastructure-less networks. In this paper, relay selection for increasing the energy efficiency of a cognitive radio network is considered. The proposed approach considers the multiple - relay selection scheme with strict outage probability constraints. Energy maximisation is posed as an optimisation problem, the solution to which shows that relay selection under outage constraints is different from the one without such a constraint. It can be observed from the simulations that energy efficiency and outage behaviour follows trade-off relations. Moreover, the original Branch and Bound algorithm has been re-designed for faster convergence. It has also been demonstrated that when strict outage constraints are imposed, the optimal number of relays selected will be more in comparison to the case where there is no outage consideration

Decentralized Dynamic Hop Selection and Power Control in Cognitive Multi-hop Relay Systems

In this paper, we consider a cognitive multi-hop relay secondary user (SU) system sharing the spectrum with some primary users (PU). The transmit power as well as the hop selection of the cognitive relays can be dynamically adapted according to the local (and causal) knowledge of the instantaneous channel state information (CSI) in the multi-hop SU system. We shall determine a low complexity, decentralized algorithm to maximize the average end-to-end throughput of the SU system with dynamic spatial reuse. The problem is challenging due to the decentralized requirement as well as the causality constraint on the knowledge of CSI. Furthermore, the problem belongs to the class of stochastic Network Utility Maximization (NUM) problems which is quite challenging. We exploit the time-scale difference between the PU activity and the CSI fluctuations and decompose the problem into a master problem and subproblems. We derive an asymptotically optimal low complexity solution using divide-and-conquer and illustrate that significant performance gain can be obtained through dynamic hop selection and power control. The worst case complexity and memory requirement of the proposed algorithm is O(M^2) and O(M^3) respectively, where $M$ is the number of SUs

Joint Spectrum Sensing and Resource Allocation for OFDM-based Transmission with a Cognitive Relay

In this paper, we investigate the joint spectrum sensing and resource allocation problem to maximize throughput capacity of an OFDM-based cognitive radio link with a cognitive relay. By applying a cognitive relay that uses decode and forward (D&F), we achieve more reliable communications, generating less interference (by needing less transmit power) and more diversity gain. In order to account for imperfections in spectrum sensing, the proposed schemes jointly modify energy detector thresholds and allocates transmit powers to all cognitive radio (CR) subcarriers, while simultaneously assigning subcarrier pairs for secondary users (SU) and the cognitive relay. This problem is cast as a constrained optimization problem with constraints on (1) interference introduced by the SU and the cognitive relay to the PUs; (2) miss-detection and false alarm probabilities and (3) subcarrier pairing for transmission on the SU transmitter and the cognitive relay and (4) minimum Quality of Service (QoS) for each CR subcarrier. We propose one optimal and two sub-optimal schemes all of which are compared to other schemes in the literature. Simulation results show that the proposed schemes achieve significantly higher throughput than other schemes in the literature for different relay situations.Comment: EAI Endorsed Transactions on Wireless Spectrum 14(1): e4 Published 13th Apr 201

Relay subset selection in cognitive networks with imperfect CSI and individual power constraints

This paper considers the relay subset selection problem in an underlay cognitive network in which two secondary users communicate assisted by a set of N potential relays. More specifically, this paper deals with the joint problem of choosing the best subset of L secondary relays and their corresponding weights which maximize the Signal-to-Interference-plus-Noise ratio (SINR) at the secondary user receiver, subject to per-relay power constraints and interference power constraints at the primary user. This problem is a combinatorial problem with a high computational burden. Nevertheless, we propose a sub-optimal technique, based on a convex relaxation of the problem, which achieves a near-optimal performance with a reduced complexity. Contrary to other approaches in the literature, the secondary relays are not limited to cooperate at full power.Peer ReviewedPostprint (author's final draft

Optimizing cooperative cognitive radio networks with opportunistic access

Optimal resource allocation for cooperative cognitive radio networks with opportunistic access to the licensed spectrum is studied. Resource allocation is based on minimizing the symbol error rate at the receiver. Both the cases of all-participate relaying and selective relaying are considered. The objective function is derived and the constraints are detailed for both scenarios. It is then shown that the objective functions and the constraints are nonlinear and nonconvex functions of the parameters of interest, that is, source and relay powers, symbol time, and sensing time. Therefore, it is difficult to obtain closed-form solutions for the optimal resource allocation. The optimization problem is then solved using numerical techniques. Numerical results show that the all-participate system provides better performance than its selection counterpart, at the cost of greater resources