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

Enhanced Compressive Wideband Frequency Spectrum Sensing for Dynamic Spectrum Access

Wideband spectrum sensing detects the unused spectrum holes for dynamic spectrum access (DSA). Too high sampling rate is the main problem. Compressive sensing (CS) can reconstruct sparse signal with much fewer randomized samples than Nyquist sampling with high probability. Since survey shows that the monitored signal is sparse in frequency domain, CS can deal with the sampling burden. Random samples can be obtained by the analog-to-information converter. Signal recovery can be formulated as an L0 norm minimization and a linear measurement fitting constraint. In DSA, the static spectrum allocation of primary radios means the bounds between different types of primary radios are known in advance. To incorporate this a priori information, we divide the whole spectrum into subsections according to the spectrum allocation policy. In the new optimization model, the minimization of the L2 norm of each subsection is used to encourage the cluster distribution locally, while the L0 norm of the L2 norms is minimized to give sparse distribution globally. Because the L0/L2 optimization is not convex, an iteratively re-weighted L1/L2 optimization is proposed to approximate it. Simulations demonstrate the proposed method outperforms others in accuracy, denoising ability, etc.Comment: 23 pages, 6 figures, 4 table. arXiv admin note: substantial text overlap with arXiv:1005.180

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. MATLAB® 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

Design and Realization of Fully-digital Microwave and Mm-wave Multi-beam Arrays with FPGA/RF-SOC Signal Processing

There has been a constant increase in data-traffic and device-connections in mobile wireless communications, which led the fifth generation (5G) implementations to exploit mm-wave bands at 24/28 GHz. The next-generation wireless access point (6G and beyond) will need to adopt large-scale transceiver arrays with a combination of multi-input-multi-output (MIMO) theory and fully digital multi-beam beamforming. The resulting high gain array factors will overcome the high path losses at mm-wave bands, and the simultaneous multi-beams will exploit the multi-directional channels due to multi-path effects and improve the signal-to-noise ratio. Such access points will be based on electronic systems which heavily depend on the integration of RF electronics with digital signal processing performed in Field programmable gate arrays (FPGA)/ RF-system-on-chip (SoC). This dissertation is directed towards the investigation and realization of fully-digital phased arrays that can produce wideband simultaneous multi-beams with FPGA or RF-SoC digital back-ends. The first proposed approach is a spatial bandpass (SBP) IIR filter-based beamformer, and is based on the concepts of space-time network resonance. A 2.4 GHz, 16-element array receiver, has been built for real-time experimental verification of this approach. The second and third approaches are respectively based on Discrete Fourier Transform (DFT) theory, and a lens plus focal planar array theory. Lens based approach is essentially an analog model of DFT. These two approaches are verified for a 28 GHz 800 MHz mm-wave implementation with RF-SoC as the digital back-end. It has been shown that for all proposed multibeam beamformer implementations, the measured beams are well aligned with those of the simulated. The proposed approaches differ in terms of their architectures, hardware complexity and costs, which will be discussed as this dissertation opens up. This dissertation also presents an application of multi-beam approaches for RF directional sensing applications to explore white spaces within the spatio-temporal spectral regions. A real-time directional sensing system is proposed to capture the white spaces within the 2.4 GHz Wi-Fi band. Further, this dissertation investigates the effect of electro-magnetic (EM) mutual coupling in antenna arrays on the real-time performance of fully-digital transceivers. Different algorithms are proposed to uncouple the mutual coupling in digital domain. The first one is based on finding the MC transfer function from the measured S-parameters of the antenna array and employing it in a Frost FIR filter in the beamforming backend. The second proposed method uses fast algorithms to realize the inverse of mutual coupling matrix via tridiagonal Toeplitz matrices having sparse factors. A 5.8 GHz 32-element array and 1-7 GHz 7-element tightly coupled dipole array (TCDA) have been employed to demonstrate the proof-of-concept of these algorithms

Bootstrapping Cognitive Radio Networks

Cognitive radio networks promise more efficient spectrum utilization by leveraging degrees of freedom and distributing data collection. The actual realization of these promises is challenged by distributed control, and incomplete, uncertain and possibly conflicting knowledge bases. We consider two problems in bootstrapping, evolving, and managing cognitive radio networks. The first is Link Rendezvous, or how separate radio nodes initially find each other in a spectrum band with many degrees of freedom, and little shared knowledge. The second is how radio nodes can negotiate for spectrum access with incomplete information. To address the first problem, we present our Frequency Parallel Blind Link Rendezvous algorithm. This approach, designed for recent generations of digital front-ends, implicitly shares vague information about spectrum occupancy early in the process, speeding the progress towards a solution. Furthermore, it operates in the frequency domain, facilitating a parallel channel rendezvous. Finally, it operates without a control channel and can rendezvous anywhere in the operating band. We present simulations and analysis on the false alarm rate for both a feature detector and a cross-correlation detector. We compare our results to the conventional frequency hopping sequence rendezvous techniques. To address the second problem, we model the network as a multi-agent system and negotiate by exchanging proposals, augmented with arguments. These arguments include information about priority status and the existence of other nodes. We show in a variety of network topologies that this process leads to solutions not otherwise apparent to individual nodes, and achieves superior network throughput, request satisfaction, and total number of connections, compared to our baselines. The agents independently formulate proposals based upon communication desires, evaluate these proposals based upon capacity constraints, create ariii guments in response to proposal rejections, and re-evaluate proposals based upon received arguments. We present our negotiation rules, messages, and protocol and demonstrate how they interoperate in a simulation environment