Performance Analysis of AF Relaying With Selection Combining in Nakagami-m Fading

This paper investigates the performance analysis of a selection combining scheme, which utilizes a variable gain amplify and forward relay over a Nakagami-m fading channel. A selection combiner at a destination node chooses the better link between a relay channel and a direct channel. We derived exact closed-form expressions for moments of signal to noise ratio (SNR), ergodic capacity, and average symbol error probability. Simulation examples confirm that our exact formulas offer a more accurate analysis tool for selection combining than other prevailing approximations without extra complexity. The derived expressions serve as a useful tool for system design due to their validity for any SNR and arbitrary system parameters

Resource Allocation in OFDM-Based Cognitive Two-Way Relay Networks

Cognitive radio (CR), nowadays, is considered as one of the most promising techniques which introduce the flexible usage of radio spectrum and improve the spectral efficiency by enabling unlicensed users to exploit the licensed spectrum in an opportunistic manner. Moreover, the two-way relay communication has attracted a great attention as it introduces a relaying scheme with a bidirectional transmission to exchange information between two nodes. This strategy assumed to improve the overall capacity, since less time slots are needed than the one-way strategy, besides extending the radio coverage range of networks. Another common technique that improves the bandwidth efficiency and spectrum utilization is the orthogonal frequency division multiplexing (OFDM) technique which exhibits a distinctive efficiency in mitigating inter-symbol interference (ISI) and combating frequency selective fading. Therefore, two-way relay CR communication among OFDM terminals can take advantage of these three techniques to boost up the capacity together with the networks quality. In this thesis, an OFDM-based amplify and forward (AF), cognitive two-way multiple-relay network is considered where two transceiver nodes exchange information via relay nodes. The full transmission happens in two time slots. In the first time slot, multiple access phase (MA), the transceiver nodes send their signals to the relay nodes while in the second time slot, broadcast phase (BC), the relay nodes broadcast the received signals to the transceivers. In this dissertation, the problem to jointly optimize the network resources is considered. The first is the transmission power of transceivers and relay nodes to ensure suitable allocated power for best signals transmission besides ensuring no harmful interference is caused to the primary system. The other important resource to be optimized is the subcarrier pairing where the first and second time slots subcarriers have to be matched such that the subcarriers with the best conditions is reserved. The final tuned resource, in this work, is the relay selection where the relay node that assures the best transition of the received signal is selected. The dual decomposition technique is applied to get the optimal resource allocation. Moreover, suboptimal algorithms are proposed to perform the resource allocation reducing, significantly, the computational complexity compared with the optimal solution with small performance degradation. Finally, simulation results of the suggested AF OFDM cognitive relaying network are shown to compare the performance gain of the different algorithms which reveals that the proposed suboptimal algorithm achieves good performance with much less computational complexity than the optimal one

Novel Physical Layer Authentication Techniques for Secure Wireless Communications

Due to the open nature of radio propagation, information security in wireless communications has been facing more challenges compared to its counterpart in wired networks. Authentication, defined as an important aspect of information security, is the process of verifying the identity of transmitters to prevent against spoofing attacks. Traditionally, secure wireless communications is achieved by relying solely upon higher layer cryptographic mechanisms. However, cryptographic approaches based on complex mathematical calculations are inefficient and vulnerable to various types of attacks. Recently, researchers have shown that the unique properties of wireless channels can be exploited for authentication enhancement by providing additional security protection against spoofing attacks. Motivated by the vulnerability of existing higher-layer security techniques and the security advantages provided by exploring the physical link properties, five novel physical layer authentication techniques to enhance the security performance of wireless systems are proposed. The first technique exploits the inherent properties of CIR to achieve robust channel-based authentication. The second and third techniques utilize a long-range channel predictor and additional multipath delay characteristics, respectively, to enhance the CIR-based authentication. The fourth technique exploits the advantages of AF cooperative relaying to improve traditional channel-based authentication. The last technique employs an embedded confidential signaling link to secure the legitimate transmissions in OFDM systems

Insights on Significant Implication on Research Approach for Enhancing 5G Network System

With the exponential growth of mobile users, there is a massive growth of data as well as novel services to support such data management. However, the existing 4G network is absolutely not meant for catering up such higher demands of bandwidth utilization as well as servicing massive users with similar Quality of service. Such problems are claimed to be effectively addressed by the adoption of 5G networking system. Although the characteristics of 5G networking are theoretically sound, still it is under the roof of the research. Therefore, this paper presents a discussion about the conventional approach as well as an approach using cognitive radio network towards addressing the frequently identified problems of energy, resource allocation, and spectral efficiency. The study collects the existing, recent researches in the domain of 5G communications from various publications. Different from existing review work, the paper also contributes towards identifying the core research findings as well as a significant research gap towards improving the communication in the 5G network system

Recent Advances in Wireless Communications and Networks

This book focuses on the current hottest issues from the lowest layers to the upper layers of wireless communication networks and provides "real-time" research progress on these issues. The authors have made every effort to systematically organize the information on these topics to make it easily accessible to readers of any level. This book also maintains the balance between current research results and their theoretical support. In this book, a variety of novel techniques in wireless communications and networks are investigated. The authors attempt to present these topics in detail. Insightful and reader-friendly descriptions are presented to nourish readers of any level, from practicing and knowledgeable communication engineers to beginning or professional researchers. All interested readers can easily find noteworthy materials in much greater detail than in previous publications and in the references cited in these chapters

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

Spectrum Optimisation in Wireless Communication Systems: Technology Evaluation, System Design and Practical Implementation

Two key technology enablers for next generation networks are examined in this thesis, namely Cognitive Radio (CR) and Spectrally Efficient Frequency Division Multiplexing (SEFDM). The first part proposes the use of traffic prediction in CR systems to improve the Quality of Service (QoS) for CR users. A framework is presented which allows CR users to capture a frequency slot in an idle licensed channel occupied by primary users. This is achieved by using CR to sense and select target spectrum bands combined with traffic prediction to determine the optimum channel-sensing order. The latter part of this thesis considers the design, practical implementation and performance evaluation of SEFDM. The key challenge that arises in SEFDM is the self-created interference which complicates the design of receiver architectures. Previous work has focused on the development of sophisticated detection algorithms, however, these suffer from an impractical computational complexity. Consequently, the aim of this work is two-fold; first, to reduce the complexity of existing algorithms to make them better-suited for application in the real world; second, to develop hardware prototypes to assess the feasibility of employing SEFDM in practical systems. The impact of oversampling and fixed-point effects on the performance of SEFDM is initially determined, followed by the design and implementation of linear detection techniques using Field Programmable Gate Arrays (FPGAs). The performance of these FPGA based linear receivers is evaluated in terms of throughput, resource utilisation and Bit Error Rate (BER). Finally, variants of the Sphere Decoding (SD) algorithm are investigated to ameliorate the error performance of SEFDM systems with targeted reduction in complexity. The Fixed SD (FSD) algorithm is implemented on a Digital Signal Processor (DSP) to measure its computational complexity. Modified sorting and decomposition strategies are then applied to this FSD algorithm offering trade-offs between execution speed and BER

Advanced receivers for distributed cooperation in mobile ad hoc networks

Mobile ad hoc networks (MANETs) are rapidly deployable wireless communications systems, operating with minimal coordination in order to avoid spectral efficiency losses caused by overhead. Cooperative transmission schemes are attractive for MANETs, but the distributed nature of such protocols comes with an increased level of interference, whose impact is further amplified by the need to push the limits of energy and spectral efficiency. Hence, the impact of interference has to be mitigated through with the use PHY layer signal processing algorithms with reasonable computational complexity. Recent advances in iterative digital receiver design techniques exploit approximate Bayesian inference and derivative message passing techniques to improve the capabilities of well-established turbo detectors. In particular, expectation propagation (EP) is a flexible technique which offers attractive complexity-performance trade-offs in situations where conventional belief propagation is limited by computational complexity. Moreover, thanks to emerging techniques in deep learning, such iterative structures are cast into deep detection networks, where learning the algorithmic hyper-parameters further improves receiver performance. In this thesis, EP-based finite-impulse response decision feedback equalizers are designed, and they achieve significant improvements, especially in high spectral efficiency applications, over more conventional turbo-equalization techniques, while having the advantage of being asymptotically predictable. A framework for designing frequency-domain EP-based receivers is proposed, in order to obtain detection architectures with low computational complexity. This framework is theoretically and numerically analysed with a focus on channel equalization, and then it is also extended to handle detection for time-varying channels and multiple-antenna systems. The design of multiple-user detectors and the impact of channel estimation are also explored to understand the capabilities and limits of this framework. Finally, a finite-length performance prediction method is presented for carrying out link abstraction for the EP-based frequency domain equalizer. The impact of accurate physical layer modelling is evaluated in the context of cooperative broadcasting in tactical MANETs, thanks to a flexible MAC-level simulato