ABSTRACTNext‐generation wireless systems facilitating better utilisation of the scarce radio spectrum have emerged as a response to inefficient and rigid spectrum assignment policies. These are comprised of intelligent radio nodes that opportunistically operate in the radio spectrum of existing primary systems, yet unwanted interference at the primary receivers is unavoidable. In order to design efficient next‐generation systems and to minimise the adverse effect of their interference, it is necessary to realise how the resulting interference impacts the performance of the primary systems. In this work, a generalised framework for the interference analysis of such a next‐generation system is presented where the next‐generation transmitters may transmit randomly with different transmit powers. The analysis is built around a model developed for the statistical representation of the interference at the primary receivers, which is then used to evaluate various performance measures of the primary system. Applications of the derived interference model in designing the next‐generation network system parameters are also demonstrated. Such approach provides a unified and generalised framework, the use of which allows a wide range of performance metrics can be evaluated. Findings of the analytical performance analyses are confirmed through extensive computer‐based Monte‐Carlo simulations. Copyright © 2014 John Wiley & Sons, Ltd.

This thesis examines interference modeling and management in small cell cognitive radio networks.A generalized unified statistical model is presented for the interference from a heterogeneous next generation network at a target receiver located at the centre of a cell. The derived model is then applied in devising a simple distributed power allocation algorithm for the next generation network nodes, and in the various performance analyses of the the coexisting systems.Cooperative communication improves the outage performance and coverage of wireless links under certain channel conditions, but is not spectrally efficient when channel conditions are favorable. A hybrid cooperation technique that can reap the diversity benefits of cooperative communication without sacrificing the multiplexing gain is proposed, and the performance of an interference temperature constrained cognitive radio network employing the proposed cooperation technique is analyzed.Next, a formulation of the power allocation problem in the cognitive interference channel is presented whereby the interference margin at the primary receivers are seen as resources to be shared optimally. A relative rate utility based power allocation algorithm that is shown to achieve favorable sum throughput is then proposed.Finally, the thesis investigates various interference coordination techniques for multi antenna cognitive radio users coexisting with multiple primary users under a restricted interference temperature constraint. Knowledge of the zero forcing beamforming techniques and the interference alignment schemes are applied to satisfy the restricted interference temperature constraint at the primary receivers while supporting significant sum rate at the secondary system.

We consider a mobile ad hoc network where packets belonging to specific transmitters arrive randomly in space and time according to a 3-D Poisson point process, and are upon arrival transmitted to their intended destinations using the carrier sensing multiple access (CSMA) MAC protocol. A packet transmission is considered successful if the received SINR is above a predefined threshold for the duration of the packet. A simple fully-distributed joint transmitter-receiver sensing scheme is proposed for the CSMA protocol to improve its performance in both non-fading and fading networks. The outage probability of this enhanced version of CSMA is derived and optimized with respect to the sensing thresholds. In order to derive a mathematical expression for the optimal sensing thresholds, the inherent hidden and exposed node problems of CSMA are considered and efficiently balanced. The performance of this improved CSMA protocol is compared to the other flavors of CSMA, and shown to bring about significant performance gain.

In the context of green technology, we propose in this work1 a new channel access method for wireless systems to reduce energy consumption. This method uses the concept of Cross Layer Design and cognitive radio blind sensing techniques to formulate a unified framework for congestion and fading analysis as well as Backoff exponent computation. It allows to acquire from the physical layer the information on the channel state using a blind spectrum sensing. Then the link layer, based on this information, detects congestion or fading situation and decides whether to transmit data or to wait. The objective of the proposed method is to achieve both high frame success rate and high energy efficiency by avoiding unsuccessful transmissions due to bad channel state. Comparaison with others published techniques shows that the proposed technique provide better results.

In practical wireless networks, the available transmission power and bandwidth are limited resources. Therefore, joint bandwidth and power allocation for wireless multi-user networks is essential in order to improve the network performance. Most of the research has focused on continuous rate, power, and bandwidth allocations in the presence of perfect channel knowledge. However, this is not the case with practical systems. In this paper, we therefore consider the issue of discrete power and bandwidth allocation for discrete-rate multi-user link adaptation with imperfect channel state information. To be more specific, we discuss how the system can be designed in such a scenario for i) sum rate maximization and ii) average power minimization in a multi-user setting. The results show that with only a few codes, we can approach the performance of systems that employ continuous (infinite) rates. We have also found that imperfect channel information at the base station affects the performance such that the sum rate is decreased and the average power consumption is increased.

In an underlay Cognitive Radio Network, multiple secondary users coexist geographically and spectrally with multiple primary users under a constraint on the maximum received interference power at the primary receivers. Given such a setting, one may ask "how to achieve maximum utility benefit at the secondary users given the imposed interference temperature constraint"? In an attempt at answering this question, we introduce a measure of the marginal secondary utility per unit primary interference (termed as relative rate utility) and propose a distributed algorithm that tries to maximize this measure. We present selected computer based Monte-Carlo simulation results, demonstrating the effectiveness of the introduced measure, and the improved performance of the proposed algorithm.

In our earlier work, we described an optimization problem and corresponding scheduling algorithm aimed at obtaining maximum throughput guarantees in wireless networks. To further improve the short-term performance, we also proposed two adaptive versions of the optimal algorithm. Results from the simulations showed that the adaptive algorithms perform significantly better than other well-known scheduling algorithms in networks based on Mobile WiMAX, HSDPA, LTE and WINNER I. However, there were several idealistic assumptions in that analysis, the most important of which is that each user estimates its carrier-to-noise ratio (CNR) perfectly, and there is no feedback delay. In practice however, the channel estimation is not perfect, and there is always some delay in the feedback channel. In this paper, we assume that a maximum a posteriori (MAP) predictor is employed for the CNR, so that the system takes the feedback delay and the channel noise into account. We then investigate the effect of imperfect channel prediction and delay on the throughput guarantees promised to all the users in the wireless network. A procedure to reduce the probability of outage in case of imperfect channel prediction is also proposed.

We revisit the widely investigated problem of maximizing the centralized sum-rate capacity in a cognitive radio network. We consider an interference-limited multi-user multi-channel environment, with a transmit sum-power constraint over all channels as well as an aggregate average interference constraint towards multiple primary users. Until very recently only sub-optimal algorithms were proposed due to the inherent non-convexity of the problem. Yet, the problem at hand has been neglected in the large-scale setting (i.e., number of nodes and channels) as usually encountered in practical scenarios. To tackle this issue, we first propose an exact mathematical adaptation of the well-known successive convex geometric programming with condensation approximations (SCVX) to better cope with large systems while keeping the convergence proof intact. Alternatively, we also propose a novel efficient low-complexity heuristic algorithm, ELCI. ELCI is an iterative approach, where the constraints are handled alternately based on the special property of the optimal solution, with a particular power update formulation based on the KKT conditions of the problem. In order to demonstrate ELCI’s efficiency we compare it to two state-of-the-art algorithms, SCVX, and the recently proposed global optimum approach, MARL. The salient highlight of ELCI is the relatively fast and very good sub-optimal performance in large-scale CR systems.

In wireless systems where transmitters are subject to a strict received power constraint, such as in underlay cognitive radio networks, cooperative communication is a promising strategy to enhance network performance, as it helps to improve the coverage area and outage performance of a network. However, this comes at the expense of increased resource utilization. To balance the performance gain against the possible over-utilization of resources, we propose a hybrid-cooperation technique for underlay cognitive radio networks, where secondary users cooperate only when required. Various performance measures of the proposed hybrid-cooperation technique are analyzed in this paper, and are also further validated numerically.

One of the key design challenges in a cognitive radio network is controlling the interference generated at coexisting primary receivers. In order to design efficient cognitive radio systems and to minimize their unwanted consequences, it is therefore necessary to effectively control the secondary interference at the primary receivers. In this paper, a generalized framework for the interference analysis of a cognitive radio network where the different secondary transmitters may transmit with different powers and transmission probabilities, is presented and various applications of this interference model are demonstrated. The findings of the analytical performance analyses are confirmed through selected computer-based Monte-Carlo simulations.

Next generation wireless systems facilitating better utilization of the scarce radio spectrum have emerged as a response to inefficient rigid spectrum assignment policies. These are comprised of intelligent radio nodes that opportunistically operate in the radio spectrum of existing legacy systems; yet unwanted interference at the legacy receivers is unavoidable. In order to design efficient next generation systems and to minimize their harmful consequences, it is necessary to realize their impact on the performance of legacy systems. In this work, a generalized framework for the ergodic capacity analysis of such legacy systems in the presence of interference from next generation systems is presented. The analysis is built around a model developed for the statistical representation of the interference at the legacy receivers, which is then used to evaluate the ergodic capacity of the legacy system. Moreover, this analysis is not limited to the context of legacy systems, and is in fact applicaple to any interference limited system. Findings of analytical performance analyses are confirmed through selected computer-based Monte-Carlo simulations.

We consider a bounded square-shaped ad hoc network scenario, within which packet arrivals are distributed randomly in space and time according to a 3-dimensional Poisson Point Process. Each packet is transmitted over a single hop to its destination, located a fixed distance away. Within this context, the outage probability of the ALOHA and CSMA protocols is derived, and we evaluate the impact of edge effects in space on the performance of MAC protocols. Our analytical expressions are verified with Monte Carlo simulations. The behavior of the network is evaluated as the system parameters, such as the node density, the physical size of the network, and the distance between each transmitter and its receiver, vary. Furthermore, the obtained results are compared to those of unbounded networks, showing that edge effects reduce the average outage probability across the network significantly, due to the lower level of interference suffered by boundary nodes.

In this paper, we investigate the spectral efficiency of vector precoding with minimum mean square error (MMSE) linear preprocessing. We restrict the discussion to the spectral efficiency of MMSE vector precoding with quadrature phase-shift keying (QPSK) signaling. Spectral efficiency is investigated by numerical simulations, and plotted as a function of the energy per bit divided by the noise spectral density Eb/N0. The optimum system load α, given as the ratio of the number of transmit and receive antennas, that maximizes spectral efficiency is obtained. Previously obtained spectral efficiency results for: Dirty paper coding (DPC), linear zero forcing (ZF), ZF vector precoding, and linear MMSE precoding are provided for comparison. We quantify the performance enhancement that MMSE vector precoding obtains in comparison to vector precoding with ZF linear preprocessing, in the low to medium Eb/N0 region. We also find that MMSE vector precoding does not significantly outperform its linear counterpart.