Interference modelling and management for cognitive radio networks

Radio spectrum is becoming increasingly scarce as more and more devices go wireless. Meanwhile, studies indicate that the assigned spectrum is not fully utilised. Cognitive radio (CR) technology is envisioned to be a promising solution to address the imbalance between spectrum scarcity and spectrum underutilisation. It improves the spectrum utilisation by reusing the unused or underutilised spectrum owned by incumbent systems (primary systems). With the introduction of CR networks, two types of interference originating from CR networks are introduced. They are the interference from CR to primary networks (CR-primary interference) and the interference among spectrum-sharing CR nodes (CR-CR interference). The interference should be well controlled and managed in order not to jeopardise the operation of the primary network and to improve the performance of CR systems. This thesis investigates the interference in CR networks by modelling and mitigating the CR-primary interference and analysing the CR-CR interference channels. Firstly, the CR-primary interference is modelled for multiple CR nodes sharing the spectrum with the primary system. The probability density functions of CR-primary interference are derived for CR networks adopting different interference management schemes. The relationship between CR operating parameters and the resulting CRprimary interference is investigated. It sheds light on the deployment of CR networks to better protect the primary system. Secondly, various interference mitigation techniques that are applicable to CR networks are reviewed. Two novel precoding schemes for CR multiple-input multipleoutput (MIMO) systems are proposed to mitigate the CR-primary interference and maximise the CR throughput. To further reduce the CR-primary interference, we also approach interference mitigation from a cross-layer perspective by jointly considering channel allocation in the media access control layer and precoding in the physical layer of CR MIMO systems. Finally, we analyse the underlying interference channels among spectrum-sharing CR users when they interfere with each other. The Pareto rate region for multi-user MIMO interference systems is characterised. Various rate region convexification schemes are examined to convexify the rate region. Then, game theory is applied to the interference system to coordinate the operation of each CR user. Nash bargaining over MIMO interference systems is characterised as well. The research presented in this thesis reveals the impact of CR operation on the resulting CR-primary network, how to mitigate the CR-primary interference and how to coordinate the spectrum-sharing CR users. It forms the fundamental basis for interference management in CR systems and consequently gives insights into the design and deployment of CR networks

Low energy indoor network : deployment optimisation

This article considers what the minimum energy indoor access point deployment is in order to achieve a certain downlink quality-of-service. The article investigates two conventional multiple-access technologies, namely: LTE-femtocells and 802.11n Wi-Fi. This is done in a dynamic multi-user and multi-cell interference network. Our baseline results are reinforced by novel theoretical expressions. Furthermore, the work underlines the importance of considering optimisation when accounting for the capacity saturation of realistic modulation and coding schemes. The results in this article show that optimising the location of access points both within a building and within the individual rooms is critical to minimise the energy consumption

Energy efficiency and interference management in long term evolution-advanced networks.

Doctoral Degree. University of KwaZulu-Natal, Durban.Cellular networks are continuously undergoing fast extraordinary evolution to overcome technological challenges. The fourth generation (4G) or Long Term Evolution-Advanced (LTE-Advanced) networks offer improvements in performance through increase in network density, while allowing self-organisation and self-healing. The LTE-Advanced architecture is heterogeneous, consisting of different radio access technologies (RATs), such as macrocell, smallcells, cooperative relay nodes (RNs), having various capabilities, and coexisting in the same geographical coverage area. These network improvements come with different challenges that affect users’ quality of service (QoS) and network performance. These challenges include; interference management, high energy consumption and poor coverage of marginal users. Hence, developing mitigation schemes for these identified challenges is the focus of this thesis. The exponential growth of mobile broadband data usage and poor networks’ performance along the cell edges, result in a large increase of the energy consumption for both base stations (BSs) and users. This due to improper RN placement or deployment that creates severe inter-cell and intracell interferences in the networks. It is therefore, necessary to investigate appropriate RN placement techniques which offer efficient coverage extension while reducing energy consumption and mitigating interference in LTE-Advanced femtocell networks. This work proposes energy efficient and optimal RN placement (EEORNP) algorithm based on greedy algorithm to assure improved and effective coverage extension. The performance of the proposed algorithm is investigated in terms of coverage percentage and number of RN needed to cover marginalised users and found to outperform other RN placement schemes. Transceiver design has gained importance as one of the effective tools of interference management. Centralised transceiver design techniques have been used to improve network performance for LTE-Advanced networks in terms of mean square error (MSE), bit error rate (BER) and sum-rate. The centralised transceiver design techniques are not effective and computationally feasible for distributed cooperative heterogeneous networks, the systems considered in this thesis. This work proposes decentralised transceivers design based on the least-square (LS) and minimum MSE (MMSE) pilot-aided channel estimations for interference management in uplink LTE-Advanced femtocell networks. The decentralised transceiver algorithms are designed for the femtocells, the macrocell user equipments (MUEs), RNs and the cell edge macrocell UEs (CUEs) in the half-duplex cooperative relaying systems. The BER performances of the proposed algorithms with the effect of channel estimation are investigated. Finally, the EE optimisation is investigated in half-duplex multi-user multiple-input multiple-output (MU-MIMO) relay systems. The EE optimisation is divided into sub-optimal EE problems due to the distributed architecture of the MU-MIMO relay systems. The decentralised approach is employed to design the transceivers such as MUEs, CUEs, RN and femtocells for the different sub-optimal EE problems. The EE objective functions are formulated as convex optimisation problems subject to the QoS and transmit powers constraints in case of perfect channel state information (CSI). The non-convexity of the formulated EE optimisation problems is surmounted by introducing the EE parameter substractive function into each proposed algorithms. These EE parameters are updated using the Dinkelbach’s algorithm. The EE optimisation of the proposed algorithms is achieved after finding the optimal transceivers where the unknown interference terms in the transmit signals are designed with the zero-forcing (ZF) assumption and estimation errors are added to improve the EE performances. With the aid of simulation results, the performance of the proposed decentralised schemes are derived in terms of average EE evaluation and found to be better than existing algorithms

Efficient radio resource management for future generation heterogeneous wireless networks

The heterogeneous deployment of small cells (e.g., femtocells) in the coverage area of the traditional macrocells is a cost-efficient solution to provide network capacity, indoor coverage and green communications towards sustainable environments in the future fifth generation (5G) wireless networks. However, the unplanned and ultra-dense deployment of femtocells with their uncoordinated operations will result in technical challenges such as severe interference, a significant increase in total energy consumption, unfairness in radio resource sharing and inadequate quality of service provisioning. Therefore, there is a need to develop efficient radio resource management algorithms that will address the above-mentioned technical challenges. The aim of this thesis is to develop and evaluate new efficient radio resource management algorithms that will be implemented in cognitive radio enabled femtocells to guarantee the economical sustainability of broadband wireless communications and users' quality of service in terms of throughput and fairness. Cognitive Radio (CR) technology with the Dynamic Spectrum Access (DSA) and stochastic process are the key technologies utilized in this research to increase the spectrum efficiency and energy efficiency at limited interference. This thesis essentially investigates three research issues relating to the efficient radio resource management: Firstly, a self-organizing radio resource management algorithm for radio resource allocation and interference management is proposed. The algorithm considers the effect of imperfect spectrum sensing in detecting the available transmission opportunities to maximize the throughput of femtocell users while keeping interference below pre-determined thresholds and ensuring fairness in radio resource sharing among users. Secondly, the effect of maximizing the energy efficiency and the spectrum efficiency individually on radio resource management is investigated. Then, an energy-efficient radio resource management algorithm and a spectrum-efficient radio resource management algorithm are proposed for green communication, to improve the probabilities of spectrum access and further increase the network capacity for sustainable environments. Also, a joint maximization of the energy efficiency and spectrum efficiency of the overall networks is considered since joint optimization of energy efficiency and spectrum efficiency is one of the goals of 5G wireless networks. Unfortunately, maximizing the energy efficiency results in low performance of the spectrum efficiency and vice versa. Therefore, there is an investigation on how to balance the trade-off that arises when maximizing both the energy efficiency and the spectrum efficiency simultaneously. Hence, a joint energy efficiency and spectrum efficiency trade-off algorithm is proposed for radio resource allocation in ultra-dense heterogeneous networks based on orthogonal frequency division multiple access. Lastly, a joint radio resource allocation with adaptive modulation and coding scheme is proposed to minimize the total transmit power across femtocells by considering the location and the service requirements of each user in the network. The performance of the proposed algorithms is evaluated by simulation and numerical analysis to demonstrate the impact of ultra-dense deployment of femtocells on the macrocell networks. The results show that the proposed algorithms offer improved performance in terms of throughput, fairness, power control, spectrum efficiency and energy efficiency. Also, the proposed algorithms display excellent performance in dynamic wireless environments

Cooperative Transmitter-Receiver Arrayed Communications

This thesis is concerned with array processing for wireless communications. In particular, cooperation between the transmitter and receiver or between systems is exploited to further improve the system performance. Based on this idea, three technical chapters are presented in this thesis. Initially in Chapter 1, an introduction including array processing, multiple-input multiple-output (MIMO) communication systems and the background of cognitive radio is presented. In Chapter 2, a novel approach for estimating the direction-of-departure (DOD) is proposed using the cooperative beamforming. This proposed approach is featured by its simplicity (beam rotation at the transmitter) and effectiveness (illustrated in terms of channel capacity). Chapter 3 is concerned with integration of spatio-temporal (ST) processing into an antenna array transmitter, given a joint transmitter-receiver system with ST processing at the receiver but spatial-only processing at the transmitter. The transmit ST processing further improves the system performance in convergence, mean-square error (MSE) and bit error rate (BER). In Chapter 4, a basic system structure for radio coexistence problem is proposed based on the concept of MIMO cognitive radio. Cooperation between the licensed radio and the cognitive radio is exploited. Optimisation of the sum channel capacity is considered as the criterion and it is solved using a multivariable water-filling algorithm. Finally, Chapter 5 concludes this thesis and gives suggestions for future work

Distributed optimisation techniques for wireless networks

Alongside the ever increasing traffic demand, the fifth generation (5G) cellular network architecture is being proposed to provide better quality of service, increased data rate, decreased latency, and increased capacity. Without any doubt, the 5G cellular network will comprise of ultra-dense networks and multiple input multiple output technologies. This will make the current centralised solutions impractical due to increased complexity. Moreover, the amount of coordination information that needs to be transported over the backhaul links will be increased. Distributed or decentralised solutions are promising to provide better alternatives. This thesis proposes new distributed algorithms for wireless networks which aim to reduce the amount of system overheads in the backhaul links and the system complexity. The analysis of conflicts amongst transmitters, and resource allocation are conducted via the use of game theory, convex optimisation, and auction theory. Firstly, game-theoretic model is used to analyse a mixed quality of service (QoS) strategic non-cooperative game (SNG), for a two-user multiple-input single-output (MISO) interference channel. The players are considered to have different objectives. Following this, the mixed QoS SNG is extended to a multicell multiuser network in terms of signal-to-interference-and-noise ratio (SINR) requirement. In the multicell multiuser setting, each transmitter is assumed to be serving real time users (RTUs) and non-real time users (NRTUs), simultaneously. A novel mixed QoS SNG algorithm is proposed, with its operating point identified as the Nash equilibrium-mixed QoS (NE-mixed QoS). Nash, Kalai-Smorodinsky, and Egalitarian bargain solutions are then proposed to improve the performance of the NE-mixed QoS. The performance of the bargain solutions are observed to be comparable to the centralised solutions. Secondly, user offloading and user association problems are addressed for small cells using auction theory. The main base station wishes to offload some of its users to privately owned small cell access points. A novel bid-wait-auction (BWA) algorithm, which allows single-item bidding at each auction round, is designed to decompose the combinatorial mathematical nature of the problem. An analysis on the existence and uniqueness of the dominant strategy equilibrium is conducted. The BWA is then used to form the forward BWA (FBWA) and the backward BWA (BBWA). It is observed that the BBWA allows more users to be admitted as compared to the FBWA. Finally, simultaneous multiple-round ascending auction (SMRA), altered SMRA (ASMRA), sequential combinatorial auction with item bidding (SCAIB), and repetitive combinatorial auction with item bidding (RCAIB) algorithms are proposed to perform user offloading and user association for small cells. These algorithms are able to allow bundle bidding. It is then proven that, truthful bidding is individually rational and leads to Walrasian equilibrium. The performance of the proposed auction based algorithms is evaluated. It is observed that the proposed algorithms match the performance of the centralised solutions when the guest users have low target rates. The SCAIB algorithm is shown to be the most preferred as it provides high admission rate and competitive revenue to the bidders

Spectral-energy efficiency trade-off for next-generation wireless communication systems

The data traffic in cellular networks has had and will experience a rapid exponential rise. Therefore, it is essential to innovate a new cellular architecture with advanced wireless technologies that can offer more capacity and enhanced spectral efficiency to manage the exponential data traffic growth. Managing such mass data traffic, however, brings up another challenge of increasing energy consumption. This is because it contributes into a growing fraction of the carbon dioxide (CO2) emission which is a global concern today due to its negative impact on the environment. This has resulted in creating a new paradigm shift towards both spectral and energy efficient orientated design for the next-generation wireless access networks. Acquiring both improved energy efficiency and spectral efficiency has, nonetheless, shown to be a difficult goal to achieve as it seems improving one is at the detriment to the other. Therefore, the trade-off between the spectral and energy efficiency is of paramount importance to assess the energy consumption in a wireless communication system required to attain a specific spectral efficiency. This thesis looks into this problem. It studies the spectral-energy efficiency tradeoff for some of the emerging wireless communication technologies which are seen as potential candidates for the fifth generation (5G) mobile cellular system. The focus is on the orthogonal frequency division multiple access (OFDMA), mobile femtocell (MFemtocell), cognitive radio (CR), and the spatial modulation (SM). Firstly, the energy-efficient resource allocation scheme for multi-user OFDMA (MU-OFDMA) system is studied. The spectral-energy efficiency trade-off is analysed under the constraint of maintaining the fairness among users. The energy-efficient optimisation problem has been formulated as integer fractional programming. We then apply an iterative method to simplify the problem to an integer linear programming (ILP) problem. Secondly, the spectral and energy efficiency for a cellular system with MFemtocell deployment is investigated using different resource partitioning schemes. Femtocells are low range, low power base stations (BSs) that improve the coverage inside a home or office building. MFemtocell adopts the femtocell solution to be deployed in public transport and emergency vehicles. Closed-form expressions for the relationships between the spectral and energy efficiency are derived for a single-user (SU) MFemtocell network. We also study the spectral efficiency for MU-MFemtocells with two opportunistic scheduling schemes. Thirdly, the spectral-energy efficiency trade-off for CR networks is analysed at both SU and MU CR systems against varying signal-to-noise ratio (SNR) values. CR is an innovative radio device that aims to utilise the spectrum more efficiently by opportunistically exploiting underutilised licensed spectrum. For the SU system, we study the required energy to achieve a specific spectral efficiency for a CR channel under two different types of power constraints in different fading environments. In this scenario, interference constraint at the primary receiver (PR) is also considered to protect the PR from harmful interference. At the system level, we study the spectral and energy efficiency for a CR network that shares the spectrum with an indoor network. Adopting the extreme-value theory, we are able to derive the average spectral efficiency of the CR network. Finally, we propose two innovative schemes to enhance the capability of (SM). SM is a recently developed technique that is employed for a low complexity multipleinput multiple-output (MIMO) transmission. The first scheme can be applied for SU MIMO (SU-MIMO) to offer more degrees of freedom than SM. Whereas the second scheme introduces a transmission structure by which the SM is adopted into a downlink MU-MIMO system. Unlike SM, both proposed schemes do not involve any restriction into the number of transmit antennas when transmitting signals. The spectral-energy efficiency trade-off for the MU-SM in the massive MIMO system is studied. In this context, we develop an iterative energy-efficient water-filling algorithm to optimises the transmit power and achieve the maximum energy efficiency for a given spectral efficiency. In summary, the research presented in this thesis reveals mathematical tools to analysis the spectral and energy efficiency for wireless communications technologies. It also offers insight to solve optimisation problems that belong to a class of problems with objectives of enhancing the energy efficiency