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

Cluster-based cooperative subcarrier sensing using antenna diversity-based weighted data fusion

Cooperative spectrum sensing (CSS) is used in cognitive radio (CR) networks to improve the spectrum sensing performance in shadow fading environments. Moreover, clustering in CR networks is used to reduce reporting time and bandwidth overhead during CSS. Thus, cluster-based cooperative spectrum sensing (CBCSS) has manifested satisfactory spectrum sensing results in harsh environments under processing constraints. On the other hand, the antenna diversity of multiple input multiple output CR systems can be exploited to further improve the spectrum sensing performance. This paper presents the CBCSS performance in a CR network which is comprised of single- as well as multiple-antenna CR systems. We give theoretical analysis of CBCSS for orthogonal frequency division multiplexing signal sensing and propose a novel fusion scheme at the fusion center which takes into account the receiver antenna diversity of the CRs present in the network. We introduce the concept of weighted data fusion in which the sensing results of different CRs are weighted proportional to the number of receiving antennas they are equipped with. Thus, the receiver diversity is used to the advantage of improving spectrum sensing performance in a CR cluster. Simulation results show that the proposed scheme outperforms the conventional CBCSS scheme

Multiband Spectrum Access: Great Promises for Future Cognitive Radio Networks

Cognitive radio has been widely considered as one of the prominent solutions to tackle the spectrum scarcity. While the majority of existing research has focused on single-band cognitive radio, multiband cognitive radio represents great promises towards implementing efficient cognitive networks compared to single-based networks. Multiband cognitive radio networks (MB-CRNs) are expected to significantly enhance the network's throughput and provide better channel maintenance by reducing handoff frequency. Nevertheless, the wideband front-end and the multiband spectrum access impose a number of challenges yet to overcome. This paper provides an in-depth analysis on the recent advancements in multiband spectrum sensing techniques, their limitations, and possible future directions to improve them. We study cooperative communications for MB-CRNs to tackle a fundamental limit on diversity and sampling. We also investigate several limits and tradeoffs of various design parameters for MB-CRNs. In addition, we explore the key MB-CRNs performance metrics that differ from the conventional metrics used for single-band based networks.Comment: 22 pages, 13 figures; published in the Proceedings of the IEEE Journal, Special Issue on Future Radio Spectrum Access, March 201

Analytic solutions to a Marcum Q-function-based integral and application in energy detection of unknown signals over multipath fading channels

This work presents analytic solutions for a useful integral in wireless communications, which involves the Marcum $Q{-}$function in combination with an exponential function and arbitrary power terms. The derived expressions have a rather simple algebraic representation which renders them convenient both analytically and computationally. Furthermore, they can be useful in wireless communications and particularly in the context of cognitive radio communications and radar systems, where this integral is often encountered. To this end, we derive novel expressions for the probability of detection in energy detection based spectrum sensing over $\eta{-}\mu$ fading channels. These expressions are given in closed-form and are subsequently employed in analyzing the effects of generalised multipath fading conditions in cognitive radio systems. As expected, it is shown that the detector is highly dependent upon the severity of fading conditions as even slight variation of the fading parameters affect the corresponding performance significantly.Comment: Latest/Preprint Versio