2 research outputs found
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Implementation of spectrum sensing techniques for cognitive radio systems
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.This work presents a method for real-time detection of secondary users at the cognitive wireless technologies base stations. Cognitive radios may hide themselves in between the primary users to avoid being charged for spectrum usage. To deal with such scenarios, a cyclostationary Fast Fourier Transform accumulation method (FAM) has been used to develop a new strategy for recognising channel users under perfect and different noise environment conditions. Channel users are tracked according to the changes in their signal parameters, such as modulation techniques. MATLABÂŽ Simulation tool was used to run various modulation signals on channels, and the obtained spectral correlation density function shows successful recognition between secondary and primary signals. We are unaware of previous efforts to use the FAM characteristics or other detection methods to make a distinction between channel users as presented in this thesis. A novel combination of both cognitive radio technology and ultra wideband technology is interdicted in this thesis, looking for an efficient and reliable spectrum sensing method to detect the presence of primary transmitters, and a number of spectrum-sensing techniques implemented in ultra wideband and cognitive radio component (UWB-CR) under different AWGN and fading settings environments. The sensing performance of different detectors is compared in conditions of probability of detection and miss detection curves. Simulation results show that the selection of detectors rely on the different fading scenarios, detector requirements and on a priori knowledge. Furthermore, result showed that the matched filter detection method is suitable for detecting signals through UWB-CR system under various fading channels. A general observation is that the matched filter detector outperforms the other detectors in all scenarios by an average of SNR=-20 dB in the level of probability of detection (Pd) , and the energy detector slightly outperforms the cyclostationary detector, in the level Pd at SNR=-20 dB. Furthermore, the thesis adapts novel detection models of cooperative and cluster cooperative wideband spectrum sensing in cognitive radio networks. In the proposed schemes, wavelet-based multi-resolution spectrum sensing and a proposed approach scheme are utilized for improving sensing performance of both models. On the other hand, cluster based cooperative spectrum sensing with soft combination Equal Gain Combination (EGC) scheme is proposed. The proposed detection models could achieve improvement of transmitter signal detection in terms of higher probability of detection and lower probability of false alarm. In the cooperative wideband spectrum sensing model, using traditional fusion rule, existing worst performance of false alarms by measurement is 78% of the sensing bands at an average SNR=5 dB; this compares with the proposed model, which is by measurement 19% false alarms of scanning spectrum at the same SNR for cluster cooperative wideband spectrum sensing. The proposed combining methods shows improvements of results with a high probability of detection (Pd) and low probability of false alarm (Pf) at an average SNR=-16 dB compared with other traditional fusion methods; this is illustrated through numerical results
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Efficient route discovery for reactive routing
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Information on the location of mobile nodes in Mobile Ad-hoc Networks (MANETs) has
the potential to significantly improve network performance. This thesis uses node location information to develop new techniques for route discovery in on-demand routing protocols such as the Ad-hoc On-Demand Distance Vector (AODV), thus making an important contribution to enhancing the experience of using mobile networks.
A Candidate Neighbours to Rebroadcast the Route Request (CNRR) approach has been
proposed to reduce the deleterious impact, known as the broadcast storm, of RREQ packets
flooding in traditional on-demand routing protocols. The main concept behind CNRR is
specifying a set of neighbours which will rebroadcast the received RREQ. This is a departure from the traditional approach of all receiving nodes rebroadcasting RREQs and has the effect of reducing the problem of redundancy from which mobile networks suffer. The proposed protocol has been developed in two phases: Closest-CNRR and Furthest-CNRR. The simulation results show that the proposed algorithms have a significant effect as they reduce the routing overhead of the AODV protocol by up to 28% compared to the C-CNRR, and by up to 17.5% compared to the F-CNRR. Notably, the proposed algorithms simultaneously achieve better throughput and less data dropping.
The Link Stability and Energy Aware protocol (LSEA) has been developed to reduce the
overhead while increasing network lifetimes. The LSEA helps to control the global
dissemination of RREQs in the network by eliminating those nodes that have a residual
energy level below a specific threshold value from participation in end-to-end routes. The proposed LSEA protocol significantly increases network lifetimes by up to 19% compared with other on-demand routing protocols while still managing to obtain the same packet delivery ratio and network throughput levels. Furthermore, merging the LSEA and CNRR concepts has the great advantage of reducing the dissemination of RREQs in the network without loss of reachability among the nodes.
This increases network lifetimes, reduces the overhead and increases the amount of data
sent and received. Accordingly, a Position-based Selective Neighbour (PSN) approach has
been proposed which combines the advantages of zoning and link stability. The results
show that the proposed technique has notable advantages over both the AODV and MAAODV
as it improves delivery ratios by 24.6% and 18.8%, respectively.Funded by National Council for Training -
Sudan and the Sudan Academy of Science