Secrecy Sum-Rates for Multi-User MIMO Regularized Channel Inversion Precoding

In this paper, we propose a linear precoder for the downlink of a multi-user MIMO system with multiple users that potentially act as eavesdroppers. The proposed precoder is based on regularized channel inversion (RCI) with a regularization parameter $\alpha$ and power allocation vector chosen in such a way that the achievable secrecy sum-rate is maximized. We consider the worst-case scenario for the multi-user MIMO system, where the transmitter assumes users cooperate to eavesdrop on other users. We derive the achievable secrecy sum-rate and obtain the closed-form expression for the optimal regularization parameter $\alpha_{\mathrm{LS}}$ of the precoder using large-system analysis. We show that the RCI precoder with $\alpha_{\mathrm{LS}}$ outperforms several other linear precoding schemes, and it achieves a secrecy sum-rate that has same scaling factor as the sum-rate achieved by the optimum RCI precoder without secrecy requirements. We propose a power allocation algorithm to maximize the secrecy sum-rate for fixed $\alpha$. We then extend our algorithm to maximize the secrecy sum-rate by jointly optimizing $\alpha$ and the power allocation vector. The jointly optimized precoder outperforms RCI with $\alpha_{\mathrm{LS}}$ and equal power allocation by up to 20 percent at practical values of the signal-to-noise ratio and for 4 users and 4 transmit antennas.Comment: IEEE Transactions on Communications, accepted for publicatio

Utilising SCM – MIMO channel model based on V-BLAST channel coding in V2V communication

Vehicular ad hoc networks VANETs has recently received significant attention in intelligent transport systems (ITS) research. It provides the driver with information regarding traffic and road conditions which is needed to reduce accidents, which will save many people's lives. In Vehicle-to-vehicle V2V communication the high-speed mobility of the nodes is the challenge, which significantly affects the reliability of communication. In this paper the utilising of SCM-MIMO channel model, (which is based on V-BLAST channel coding) is present to evaluate the performance of the PHY layer in V2V communication. The simulation results observed that the SCM model can overcome the propagation issues such as path loss, multipath fading and shadowing loss. The simulation considered three different environments, high, medium and low disruptions in urban traffic

Linear and Dirty-Paper Techniques for the Multiuser MIMO Downlink

Multi-input, multi-output (MIMO) communications systems have attracted considerable attention over the past decade, mostly for single-user, point-to-point scenarios. The multiple-user MIMO case has attracted less attention, and most of the research on this problem has focused on uplink communications. Only recently has the multi-user MIMO downlink been addressed, beginning with information-theoretic capacity results [1–5], and followed by prac-tical implementations, including those based on linear techniques [6, 7] and non-linear pre-coding [8–11]. In this chapter we review these techniques and discuss some important open problems

Modeling and analyzing wireless networks using stochastic geometry

Over the past decade, stochastic geometric models, and most notably the planar Poisson point process (PPP) model, have become popular for the analysis of spectral efficiency in wireless networks, in both the D2D and the cellular contexts [1]. By modeling base station (BS) and user locations as spatial point processes, stochastic geometry has recently been recognized as a tractable and efficient analytical tool to quantify key performance metrics. This tool provides a natural way of defining and computing macroscopic properties of multiuser information theory. These properties are obtained by averaging over all node patterns found in a large random network of the Euclidean plane. For example, some key performance metrics such as signal to interference and noise ratio and data rate depend on the network geometric configurations. This tool has thus been widely adopted for analyzing the network performance and broadening network design. This thesis proposes new models to represent several new scenarios. Three main scenarios are considered: 3-D inbuilding networks, MIMO adhoc networks, and multihop communication under mmWave networks. To do so, mathematical tools such as Poisson point processes, Poisson line processes, Boolean models and Poisson bipolar models are used. Each model is 1) generative in that it has a clear physical interpretation, 2) leads to explicit analytical representations of important wireless performance metrics, and 3) highly parametric, with parameters expressing the geometric characteristic of the elements of networks. Physical interpretations from these models are quite different from previous results. The core of this thesis is focused on the effects of correlated shadowing. Shadowing is the effect that the received signal power fluctuates due to objects obstructing the propagation path. By introducing an independent shadowing term over links, it is possible to model the effect of shadow fading. Most previous papers analyzing urban networks assume that shadowing fields are independent over links. With this assumption, it is possible to derive simple closed-form expressions of important network performance metrics. However, this assumption cannot capture that shadowing fields are spatially correlated. This thesis goes beyond the independent shadowing approximation and analyzes the effects of correlated shadowing on various performance metricsElectrical and Computer Engineerin

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

Power-efficient distributed resource allocation under goodput QoS constraints for heterogeneous networks

This work proposes a distributed resource allocation (RA) algorithm for packet bit-interleaved coded OFDM transmissions in the uplink of heterogeneous networks (HetNets), characterized by small cells deployed over a macrocell area and sharing the same band. Every user allocates its transmission resources, i.e., bits per active subcarrier, coding rate, and power per subcarrier, to minimize the power consumption while both guaranteeing a target quality of service (QoS) and accounting for the interference inflicted by other users transmitting over the same band. The QoS consists of the number of information bits delivered in error-free packets per unit of time, or goodput (GP), estimated at the transmitter by resorting to an efficient effective SNR mapping technique. First, the RA problem is solved in the point-to-point case, thus deriving an approximate yet accurate closed-form expression for the power allocation (PA). Then, the interference-limited HetNet case is examined, where the RA problem is described as a non-cooperative game, providing a solution in terms of generalized Nash equilibrium. Thanks to the closed-form of the PA, the solution analysis is based on the best response concept. Hence, sufficient conditions for existence and uniqueness of the solution are analytically derived, along with a distributed algorithm capable of reaching the game equilibrium

A channel model and coding for vehicle to vehicle communication based on a developed V-SCME

Over the recent years, VANET communication has attracted a lot of attention due to its potential in facilitating the implementation of 'Intelligent Transport System'. Vehicular applications need to be completely tested before deploying them in the real world. In this context, VANET simulations would be preferred in order to evaluate and validate the proposed model, these simulations are considered inexpensive compared to the real world (hardware) tests. The development of a more realistic simulation environment for VANET is critical in ensuring high performance. Any environment required for simulating VANET, needs to be more realistic and include a precise representation of vehicle movements, as well as passing signals among different vehicles. In order to achieve efficient results that reflect the reality, a high computational power during the simulation is needed which consumes a lot of time. The existing simulation tools could not simulate the exact physical conditions of the real world, so results can be viewed as unsatisfactory when compared with real world experiments. This thesis describes two approaches to improve such vehicle to vehicle communication. The first one is based on the development of an already existing approach, the Spatial Channel Model Extended (SCME) for cellular communication which is a verified, validated and well-established communication channel model. The new developed model, is called Vehicular - Spatial Channel Model Extended (V-SCME) and can be utilised for Vehicle to Vehicle communication. V-SCME is a statistical channel model which was specifically developed and configured to satisfy the requirements of the highly dynamic network topology such as vehicle to vehicle communication. V-SCME provides a precise channel coefficients library for vehicle to vehicle communication for use by the research community, so as to reduce the overall simulation time. The second approach is to apply V-BLAST (MIMO) coding which can be implemented with vehicle to vehicle communication and improve its performance over the V-SCME. The V- SCME channel model with V-BLAST coding system was used to improve vehicle to vehicle physical layer performance, which is a novel contribution. Based on analysis and simulations, it was found that the developed channel model V-SCME is a good solution to satisfy the requirements of vehicle to vehicle communication, where it has considered a lot of parameters in order to obtain more realistic results compared with the real world tests. In addition, V-BLAST (MIMO) coding with the V-SCME has shown an improvement in the bit error rate. The obtained results were intensively compared with other types of MIMO coding

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

Directional Link Management using In-Band Full-Duplex Free Space Optical Transceivers for Aerial Nodes

Free-space optical (FSO) communication has become very popular for wireless applications to complement and, in some cases, replace legacy radio-frequency for advantages like unlicensed band, spatial reuse, and enhanced security. Even though FSO can achieve very high bit-rate (tens of Gbps), range limitation due to high attenuation and weather dependency has always restricted its practical implementation to indoor application like data centers and outdoor application like Project Loon. Building-to-building communication, smart cars, and airborne drones are potential futuristic wireless communication sectors for mobile ad-hoc FSO networking. Increasing social media usage demands high-speed mobile connectivity for applications like video call and live video stream on the go. For these scenarios, implementation of in-band full-duplex FSO (IBFD-FSO) transceivers will potentially double the network capacity to improve performance and reliability of the communication link. In this work, we focus on implementing prototypes of FSO transceivers on mobile platform using both off-the-shelf and customized components. Current goal is to implement a prototype of IBFD-FSO transceiver using VCSEL as transmitter and PIN photodiode as receiver at 900 nm wavelength. We are considering atmospheric attenuation, FSO beam propagation model, geometry, and tiling of the components to optimize the link performance while keeping the package low-cost and mobile, ensuring connectivity to mass population. Eventually, our goal is to have communication between multiple airborne drones through IBFD-FSO transceivers by discovering each other and maintaining established link. Applications of this research is not only limited to the conceived idea of smart cities, but it can also have real impact on disaster management in times of wildfire or hurricane