Performance analysis of energy detector over generalised wireless channels in cognitive radio

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London.This thesis extensively analyses the performance of an energy detector which is widely employed to perform spectrum sensing in cognitive radio over different generalised channel models. In this analysis, both the average probability of detection and the average area under the receiver operating characteristic curve (AUC) are derived using the probability density function of the received instantaneous signal to noise ratio (SNR). The performance of energy detector over an ŋ --- µ fading, which is used to model the Non-line-of-sight (NLoS) communication scenarios is provided. Then, the behaviour of the energy detector over к --- µ shadowed fading channel, which is a composite of generalized multipath/shadowing fading channel to model the lineof- sight (LoS) communication medium is investigated. The analysis of the energy detector over both ŋ --- µ and к --- µ shadowed fading channels are then extended to include maximal ratio combining (MRC), square law combining (SLC) and square law selection (SLS) with independent and non-identically (i:n:d) diversity branches. To overcome the problem of mathematical intractability in analysing the energy detector over i:n:d composite fading channels with MRC and selection combining (SC), two different unified statistical properties models for the sum and the maximum of mixture gamma (MG) variates are derived. The first model is limited by the value of the shadowing severity index, which should be an integer number and has been employed to study the performance of energy detector over composite α --- µ /gamma fading channel. This channel is proposed to represent the non-linear prorogation environment. On the other side, the second model is general and has been utilised to analyse the behaviour of energy detector over composite ŋ --- µ /gamma fading channel. Finally, a special filter-bank transform which is called slantlet packet transform (SPT) is developed and used to estimate the uncertain noise power. Moreover, signal denoising based on hybrid slantlet transform (HST) is employed to reduce the noise impact on the performance of energy detector. The combined SPT-HST approach improves the detection capability of energy detector with 97% and reduces the total computational complexity by nearly 19% in comparison with previously implemented work using filter-bank transforms. The aforementioned percentages are measured at specific SNR, number of selected samples and levels of signal decompositionMartyrs Foundatio

Performance analysis for industrial wireless networks

Industrial wireless networks operate in harsher and noisier environments compared to traditional wireless networks, while demanding high reliability and low latency. These requirements, combined with the constant need for better coverage, higher data rates and overall seamless user experience call for a paradigm shift in communication in regards to the previous generations of technologies used. Cooperative diversity is one such approach. The main focus of this thesis is on the performance analysis of cooperative wireless networks set in industrial environments – where the network, apart from additive white Gaussian noise, is subject to multipath fading and shadowing, and/or temporary random blockage effects. In these scenarios, in order to achieve specific performance metrics such as error rates or outage probabilities, existing cooperative strategies are aided by protocols in the channel between the cooperating nodes. Moreover, pair-wise analysis investigates the correlation of multiple data flows. Building upon existing repetition protocols, outage performance of a network subject to fading and shadowing is observed, and the effects of fading and shadowing severity, network dimension, average signal-to-noise ratio values and packet length are discussed. Special cases are also observed, in which the composite fading channel is reduced to several familiar propagation environments, unifying the analysis. Afterwards, the analysis of more complex protocols is presented, taking into account random blockage in the channels between cooperating nodes. A novel, threshold-based internode protocol is introduced, which improves performance by listening to the transmissions and choosing whether to send a packet immediately or after a waiting period. As these two periods are close, the effect of temporal correlation is also investigated. Apart from the exact outage probability expressions, simpler asymptotic expressions, with and without blockage, are derived as well, giving a better insight on the network behaviour at high average signal-to-noise ratio regimes. Both outage probability and packet error rate can be also improved by adding automatic repeat request schemes in the channel between cooperating nodes, which again utilize the internode channels by re-sending data until it can be successfully decoded. Error-free communication can be achieved, but at a delay cost. Nevertheless, a trade-off between performance gains and delays remains, and can therefore be used for designing wireless networks with different requirements – error-free or low-latency. Finally, joint outage performance is investigated. Using a generic approach, which can be applied to any sort of data where multiple sources are communicating over wireless networks, pair-wise behaviour is investigated. As a result, any multi-route diversity type of scheme will have this sort of behaviour, since particular point-to-point relay links are being shared by source nodes. This in turn means that the performance of those flows will be correlated. For higher layers, there is a difference in the behaviour, meaning that when errors are correlated, data flows start behaving correlated as well. As a result, negative acknowledgements may start to correlate as well. All of this contributes to the network behaving in a correlated way, i.e., when something happens, it tends to happen to more than one data flow

Applications of Stochastic Ordering to Wireless Communications

Stochastic orders are binary relations defined on probability distributions which capture intuitive notions like being larger or being more variable. This paper introduces stochastic ordering of instantaneous SNRs of fading channels as a tool to compare the performance of communication systems over different channels. Stochastic orders unify existing performance metrics such as ergodic capacity, and metrics based on error rate functions for commonly used modulation schemes through their relation with convex, and completely monotonic (c.m.) functions. Toward this goal, performance metrics such as instantaneous error rates of M-QAM and M-PSK modulations are shown to be c.m. functions of the instantaneous SNR, while metrics such as the instantaneous capacity are seen to have a completely monotonic derivative (c.m.d.). It is shown that the commonly used parametric fading distributions for modeling line of sight (LoS), exhibit a monotonicity in the LoS parameter with respect to the stochastic Laplace transform order. Using stochastic orders, average performance of systems involving multiple random variables are compared over different channels, even when closed form expressions for such averages are not tractable. These include diversity combining schemes, relay networks, and signal detection over fading channels with non-Gaussian additive noise, which are investigated herein. Simulations are also provided to corroborate our results.Comment: 25 pages, 10 figures, Submitted to the IEEE transactions on wireless communication