Optimising Cooperative Spectrum Sensing in Cognitive Radio Networks Using Interference Alignment and Space-Time Coding

In this thesis, the process of optimizing Cooperative Spectrum Sensing in Cognitive Radio has been investigated in fast-fading environments where simulation results have shown that its performance is limited by the Probability of Reporting Errors. By proposing a transmit diversity scheme using Differential space-time block codes (D-STBC) where channel state information (CSI) is not required and regarding multiple pairs of Cognitive Radios (CR’s) with single antennas as a virtual MIMO antenna arrays in multiple clusters, Differential space-time coding is applied for the purpose of decision reporting over Rayleigh channels. Both Hard and Soft combination schemes were investigated at the fusion center to reveal performance advantages for Hard combination schemes due to their minimal bandwidth requirements and simplistic implementation. The simulations results show that this optimization process achieves full transmit diversity, albeit with slight performance degradation in terms of power with improvements in performance when compared to conventional Cooperative Spectrum Sensing over non-ideal reporting channels. Further research carried out in this thesis shows performance deficits of Cooperative Spectrum Sensing due to interference on sensing channels of Cognitive Radio. Interference Alignment (IA) being a revolutionary wireless transmission strategy that reduces the impact of interference seems well suited as a strategy that can be used to optimize the performance of Cooperative Spectrum Sensing. The idea of IA is to coordinate multiple transmitters so that their mutual interference aligns at their receivers, facilitating simple interference cancellation techniques. Since its inception, research efforts have primarily been focused on verifying IA’s ability to achieve the maximum degrees of freedom (an approximation of sum capacity), developing algorithms for determining alignment solutions and designing transmission strategies that relax the need for perfect alignment but yield better performance. With the increased deployment of wireless services, CR’s ability to opportunistically sense and access the unused licensed frequency spectrum, without causing harmful interference to the licensed users becomes increasingly diminished, making the concept of introducing IA in CR a very attractive proposition. For a multiuser multiple-input–multiple-output (MIMO) overlay CR network, a space-time opportunistic IA (ST-OIA) technique has been proposed that allows spectrum sharing between a single primary user (PU) and multiple secondary users (SU) while ensuring zero interference to the PUs. With local CSI available at both the transmitters and receivers of SUs, the PU employs a space-time WF (STWF) algorithm to optimize its transmission and in the process, frees up unused eigenmodes that can be exploited by the SU. STWF achieves higher performance than other WF algorithms at low to moderate signal-to-noise ratio (SNR) regimes, which makes it ideal for implementation in CR networks. The SUs align their transmitted signals in such a way their interference impairs only the PU’s unused eigenmodes. For the multiple SUs to further exploit the benefits of Cooperative Spectrum Sensing, it was shown in this thesis that IA would only work when a set of conditions were met. The first condition ensures that the SUs satisfy a zero interference constraint at the PU’s receiver by designing their post-processing matrices such that they are orthogonal to the received signal from the PU link. The second condition ensures a zero interference constraint at both the PU and SUs receivers i.e. the constraint ensures that no interference from the SU transmitters is present at the output of the post-processing matrices of its unintended receivers. The third condition caters for the multiple SUs scenario to ensure interference from multiple SUs are aligned along unused eigenmodes. The SU system is assumed to employ a time division multiple access (TDMA) system such that the Principle of Reciprocity is employed towards optimizing the SUs transmission rates. Since aligning multiple SU transmissions at the PU is always limited by availability of spatial dimensions as well as typical user loads, the third condition proposes a user selection algorithm by the fusion centre (FC), where the SUs are grouped into clusters based on their numbers (i.e. two SUs per cluster) and their proximity to the FC, so that they can be aligned at each PU-Rx. This converts the cognitive IA problem into an unconstrained standard IA problem for a general cognitive system. Given the fact that the optimal power allocation algorithms used to optimize the SUs transmission rates turns out to be an optimal beamformer with multiple eigenbeams, this work initially proposes combining the diversity gain property of STBC, the zero-forcing function of IA and beamforming to optimize the SUs transmission rates. However, this solution requires availability of CSI, and to eliminate the need for this, this work then combines the D-STBC scheme with optimal IA precoders (consisting of beamforming and zero-forcing) to maximize the SUs data rates

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

Distributed space time block coding and application in cooperative cognitive relay networks

The design and analysis of various distributed space time block coding schemes for cooperative relay networks is considered in this thesis. Rayleigh frequency flat and selective fading channels are assumed to model the links in the networks, and interference suppression techniques together with an orthogonal frequency division multiplexing (OFDM) type transmission approach are employed to mitigate synchronization errors at the destination node induced by the different delays through the relay nodes. Closed-loop space time block coding is first considered in the context of decode-and-forward (regenerative) networks. In particular, quasi orthogonal and extended orthogonal coding techniques are employed for transmission from four relay nodes and parallel interference cancellation detection is exploited to mitigate synchronization errors. Availability of a direct link between the source and destination nodes is studied. Outer coding is then added to gain further improvement in end-to-end performance and amplify-and-forward (non regenerative) type networks together with distributed space time coding are considered to reduce relay node complexity. A novel detection scheme is then proposed for decode-and-forward and amplify-and-forward networks with closed-loop extended orthogonal coding and closed-loop quasi-orthogonal coding which reduce the computational complexity of the parallel interference cancellation. The near-optimum detector is presented for relay nodes with single or dual antennas. End-to-end bit error rate simulations confirm the potential of the approach and its ability to mitigate synchronization errors

Distributed space-time-frequency block code for cognitive wireless relay networks

In this study, the authors consider cooperative transmission in cognitive wireless relay networks (CWRNs) over frequency-selective fading channels. They propose a new distributed space-time–frequency block code (DSTFBC) for a two-hop non-regenerative CWRN, where a primary source node and multiple secondary source nodes convey information data to their desired primary destination node and multiple secondary destination nodes via multiple cognitive relay nodes with dynamic spectrum access. The proposed DSTFBC is designed to achieve spatial diversity gain as well as allow for low-complexity decoupling detection at the receiver. Pairwise error probability is then analysed to study the achievable diversity gain of the proposed DSTFBC for different channel models including Rician fading and mixed Rayleigh–Rician fading

Distributed space-time-frequency block code for cognitive wireless relay networks

In this study, the authors consider cooperative transmission in cognitive wireless relay networks (CWRNs) over frequency-selective fading channels. They propose a new distributed space-time–frequency block code (DSTFBC) for a two-hop non-regenerative CWRN, where a primary source node and multiple secondary source nodes convey information data to their desired primary destination node and multiple secondary destination nodes via multiple cognitive relay nodes with dynamic spectrum access. The proposed DSTFBC is designed to achieve spatial diversity gain as well as allow for low-complexity decoupling detection at the receiver. Pairwise error probability is then analysed to study the achievable diversity gain of the proposed DSTFBC for different channel models including Rician fading and mixed Rayleigh–Rician fading

Adaptive Coded Modulation Classification and Spectrum Sensing for Cognitive Radio Systems. Adaptive Coded Modulation Techniques for Cognitive Radio Using Kalman Filter and Interacting Multiple Model Methods

The current and future trends of modern wireless communication systems place heavy demands on fast data transmissions in order to satisfy end users’ requirements anytime, anywhere. Such demands are obvious in recent applications such as smart phones, long term evolution (LTE), 4 & 5 Generations (4G & 5G), and worldwide interoperability for microwave access (WiMAX) platforms, where robust coding and modulations are essential especially in streaming on-line video material, social media and gaming. This eventually resulted in extreme exhaustion imposed on the frequency spectrum as a rare natural resource due to stagnation in current spectrum management policies. Since its advent in the late 1990s, cognitive radio (CR) has been conceived as an enabling technology aiming at the efficient utilisation of frequency spectrum that can lead to potential direct spectrum access (DSA) management. This is mainly attributed to its internal capabilities inherited from the concept of software defined radio (SDR) to sniff its surroundings, learn and adapt its operational parameters accordingly. CR systems (CRs) may commonly comprise one or all of the following core engines that characterise their architectures; namely, adaptive coded modulation (ACM), automatic modulation classification (AMC) and spectrum sensing (SS). Motivated by the above challenges, this programme of research is primarily aimed at the design and development of new paradigms to help improve the adaptability of CRs and thereby achieve the desirable signal processing tasks at the physical layer of the above core engines. Approximate modelling of Rayleigh and finite state Markov channels (FSMC) with a new concept borrowed from econometric studies have been approached. Then insightful channel estimation by using Kalman filter (KF) augmented with interacting multiple model (IMM) has been examined for the purpose of robust adaptability, which is applied for the first time in wireless communication systems. Such new IMM-KF combination has been facilitated in the feedback channel between wireless transmitter and receiver to adjust the transmitted power, by using a water-filling (WF) technique, and constellation pattern and rate in the ACM algorithm. The AMC has also benefited from such IMM-KF integration to boost the performance against conventional parametric estimation methods such as maximum likelihood estimate (MLE) for channel interrogation and the estimated parameters of both inserted into the ML classification algorithm. Expectation-maximisation (EM) has been applied to examine unknown transmitted modulation sequences and channel parameters in tandem. Finally, the non-parametric multitaper method (MTM) has been thoroughly examined for spectrum estimation (SE) and SS, by relying on Neyman-Pearson (NP) detection principle for hypothesis test, to allow licensed primary users (PUs) to coexist with opportunistic unlicensed secondary users (SUs) in the same frequency bands of interest without harmful effects. The performance of the above newly suggested paradigms have been simulated and assessed under various transmission settings and revealed substantial improvements