Resource allocation and feedback in wireless multiuser networks

This thesis focuses on the design of algorithms for resource allocation and feedback in wireless multiuser and heterogeneous networks. In particular, three key design challenges expected to have a major impact on future wireless networks are considered: cross-layer scheduling; structured quantization codebook design for MU-MIMO networks with limited feedback; and resource allocation to provide physical layer security. The first design challenge is cross-layer scheduling, where policies are proposed for two network architectures: user scheduling in single-cell multiuser networks aided by a relay; and base station (BS) scheduling in CoMP. These scheduling policies are then analyzed to guarantee satisfaction of three performance metrics: SEP; packet delay; and packet loss probability (PLP) due to buffer overflow. The concept of the τ-achievable PLP region is also introduced to explicitly describe the tradeoff in PLP between different users. The second design challenge is structured quantization codebook design in wireless networks with limited feedback, for both MU-MIMO and CoMP. In the MU-MIMO network, two codebook constructions are proposed, which are based on structured transformations of a base codebook. In the CoMP network, a low-complexity construction is proposed to solve the problem of variable codebook dimensions due to changes in the number of coordinated BSs. The proposed construction is shown to have comparable performance with the standard approach based on a random search, while only requiring linear instead of exponential complexity. The final design challenge is resource allocation for physical layer security in MU-MIMO. To guarantee physical layer security, the achievable secrecy sum-rate is explicitly derived for the regularized channel inversion (RCI) precoder. To improve performance, power allocation and precoder design are jointly optimized using a new algorithm based on convex optimization techniques

Resource allocation and feedback in wireless multiuser networks

This thesis focuses on the design of algorithms for resource allocation and feedback in wireless multiuser and heterogeneous networks. In particular, three key design challenges expected to have a major impact on future wireless networks are considered: cross-layer scheduling; structured quantization codebook design for MU-MIMO networks with limited feedback; and resource allocation to provide physical layer security. The first design challenge is cross-layer scheduling, where policies are proposed for two network architectures: user scheduling in single-cell multiuser networks aided by a relay; and base station (BS) scheduling in CoMP. These scheduling policies are then analyzed to guarantee satisfaction of three performance metrics: SEP; packet delay; and packet loss probability (PLP) due to buffer overflow. The concept of the τ-achievable PLP region is also introduced to explicitly describe the tradeoff in PLP between different users. The second design challenge is structured quantization codebook design in wireless networks with limited feedback, for both MU-MIMO and CoMP. In the MU-MIMO network, two codebook constructions are proposed, which are based on structured transformations of a base codebook. In the CoMP network, a low-complexity construction is proposed to solve the problem of variable codebook dimensions due to changes in the number of coordinated BSs. The proposed construction is shown to have comparable performance with the standard approach based on a random search, while only requiring linear instead of exponential complexity. The final design challenge is resource allocation for physical layer security in MU-MIMO. To guarantee physical layer security, the achievable secrecy sum-rate is explicitly derived for the regularized channel inversion (RCI) precoder. To improve performance, power allocation and precoder design are jointly optimized using a new algorithm based on convex optimization techniques

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

Design and performance analysis of optical attocell networks

The exponentially increasing demand for high-speed wireless communications will no longer be satisfied by the traditional radio frequency (RF) in the near future due to its limited spectrum and overutilization. To resolve this imminent issue, industrial and research communities have been looking into alternative technologies for communication. Among them, visible light communication (VLC) has attracted much attention because it utilizes the unlicensed, free and safe spectrum, whose bandwidth is thousand times larger than the entire RF spectrum. Moreover, VLC can be integrated into existing lighting systems to offer a dual-purpose, cost-effective and energy-efficient solution for next-generation small-cell networks (SCNs), giving birth to the concept of optical attocell networks. Most relevant works in the literature rely on system simulations to quantify the performance of attocell networks, which suffer from high computational complexity and provide limited insights about the network. Mathematical tools, on the other hand, are more tractable and scalable and are shown to closely approximate practical systems. The presented work utilizes stochastic geometry for downlink evaluation of optical attocell networks, where the co-channel interference (CCI) surpasses noise and becomes the limiting factor of the link throughput. By studying the moment generating function (MGF) of the aggregate interference, a theoretical framework for modeling the distribution of signal-to-interference-plus-noise ratio (SINR) is presented, which allows important performance metrics such as the coverage probability and link throughput to be derived. Depending on the source of interference, CCI can be classified into two categories: inter-cell interference (ICI) and intra-cell interference. In this work, both types of interference are characterized, based on which effective interference mitigation techniques such as the coordinated multipoint (CoMP), power-domain multiplexing and successive interference cancellation (SIC) are devised. The proposed mathematical framework is applicable to attocell networks with and without such interference mitigation techniques. Compared to RF networks, optical attocell networks are inherently more secure in the physical layer because visible light does not penetrate through opaque walls. This work analytically quantifies the physical-layer security of attocell networks from an information-theoretic point of view. Secrecy enhancement techniques such as AP cooperation and eavesdropper-free protected zones are also discussed. It is shown that compared to AP cooperation, implementing secrecy protected zones is more effective and it can contribute significantly to the network security

Data Collection in Two-Tier IoT Networks with Radio Frequency (RF) Energy Harvesting Devices and Tags

The Internet of things (IoT) is expected to connect physical objects and end-users using technologies such as wireless sensor networks and radio frequency identification (RFID). In addition, it will employ a wireless multi-hop backhaul to transfer data collected by a myriad of devices to users or applications such as digital twins operating in a Metaverse. A critical issue is that the number of packets collected and transferred to the Internet is bounded by limited network resources such as bandwidth and energy. In this respect, IoT networks have adopted technologies such as time division multiple access (TDMA), signal interference cancellation (SIC) and multiple-input multiple-output (MIMO) in order to increase network capacity. Another fundamental issue is energy. To this end, researchers have exploited radio frequency (RF) energy-harvesting technologies to prolong the lifetime of energy constrained sensors and smart devices. Specifically, devices with RF energy harvesting capabilities can rely on ambient RF sources such as access points, television towers, and base stations. Further, an operator may deploy dedicated power beacons that serve as RF-energy sources. Apart from that, in order to reduce energy consumption, devices can adopt ambient backscattering communication technologies. Advantageously, backscattering allows devices to communicate using negligible amount of energy by modulating ambient RF signals. To address the aforementioned issues, this thesis first considers data collection in a two-tier MIMO ambient RF energy-harvesting network. The first tier consists of routers with MIMO capability and a set of source-destination pairs/flows. The second tier consists of energy harvesting devices that rely on RF transmissions from routers for energy supply. The problem is to determine a minimum-length TDMA link schedule that satisfies the traffic demand of source-destination pairs and energy demand of energy harvesting devices. It formulates the problem as a linear program (LP), and outlines a heuristic to construct transmission sets that are then used by the said LP. In addition, it outlines a new routing metric that considers the energy demand of energy harvesting devices to cope with routing requirements of IoT networks. The simulation results show that the proposed algorithm on average achieves 31.25% shorter schedules as compared to competing schemes. In addition, the said routing metric results in link schedules that are at most 24.75% longer than those computed by the LP