Joint Cooperative Spectrum Sensing and MAC Protocol Design for Multi-channel Cognitive Radio Networks

In this paper, we propose a semi-distributed cooperative spectrum sen sing (SDCSS) and channel access framework for multi-channel cognitive radio networks (CRNs). In particular, we c onsider a SDCSS scheme where secondary users (SUs) perform sensing and exchange sensing outcomes with ea ch other to locate spectrum holes. In addition, we devise the p -persistent CSMA-based cognitive MAC protocol integrating the SDCSS to enable efficient spectrum sharing among SUs. We then perform throughput analysis and develop an algorithm to determine the spectrum sensing and access parameters to maximize the throughput for a given allocation of channel sensing sets. Moreover, we consider the spectrum sensing set optimization problem for SUs to maxim ize the overall system throughput. We present both exhaustive search and low-complexity greedy algorithms to determine the sensing sets for SUs and analyze their complexity. We also show how our design and analysis can be extended to consider reporting errors. Finally, extensive numerical results are presented to demonstrate the sig nificant performance gain of our optimized design framework with respect to non-optimized designs as well as the imp acts of different protocol parameters on the throughput performance.Comment: accepted for publication EURASIP Journal on Wireless Communications and Networking, 201

General analytical framework for cooperative sensing and access trade-off optimization

In this paper, we investigate the joint cooperative spectrum sensing and access design problem for multi-channel cognitive radio networks. A general heterogeneous setting is considered where the probabilities that different channels are available, SNRs of the signals received at secondary users (SUs) due to transmissions from primary users (PUs) for different users and channels can be different. We assume a cooperative sensing strategy with a general a-out-of-b aggregation rule and design a synchronized MAC protocol so that SUs can exploit available channels. We analyze the sensing performance and the throughput achieved by the joint sensing and access design. Based on this analysis, we develop algorithms to find optimal parameters for the sensing and access protocols and to determine channel assignment for SUs to maximize the system throughput. Finally, numerical results are presented to verify the effectiveness of our design and demonstrate the relative performance of our proposed algorithms and the optimal ones.Comment: arXiv admin note: text overlap with arXiv:1404.167

MULTI USER COOPERATION SPECTRUM SENSING IN WIRELESS COGNITIVE RADIO NETWORKS

With the rapid proliferation of new wireless communication devices and services, the demand for the radio spectrum is increasing at a rapid rate, which leads to making the spectrum more and more crowded. The limited available spectrum and the inefficiency in the spectrum usage have led to the emergence of cognitive radio (CR) and dynamic spectrum access (DSA) technologies, which enable future wireless communication systems to exploit the empty spectrum in an opportunistic manner. To do so, future wireless devices should be aware of their surrounding radio environment in order to adapt their operating parameters according to the real-time conditions of the radio environment. From this viewpoint, spectrum sensing is becoming increasingly important to new and future wireless communication systems, which is designed to monitor the usage of the radio spectrum and reliably identify the unused bands to enable wireless devices to switch from one vacant band to another, thereby achieving flexible, reliable, and efficient spectrum utilisation. This thesis focuses on issues related to local and cooperative spectrum sensing for CR networks, which need to be resolved. These include the problems of noise uncertainty and detection in low signal to noise ratio (SNR) environments in individual spectrum sensing. In addition to issues of energy consumption, sensing delay and reporting error in cooperative spectrum sensing. In this thesis, we investigate how to improve spectrum sensing algorithms to increase their detection performance and achieving energy efficiency. To this end, first, we propose a new spectrum sensing algorithm based on energy detection that increases the reliability of individual spectrum sensing. In spite of the fact that the energy detection is still the most common detection mechanism for spectrum sensing due to its simplicity. Energy detection does not require any prior knowledge of primary signals, but has the drawbacks of threshold selection, and poor performance due to noise uncertainty especially at low SNR. Therefore, a new adaptive optimal energy detection algorithm (AOED) is presented in this thesis. In comparison with the existing energy detection schemes the detection performance achieved through AOED algorithm is higher. Secondly, as cooperative spectrum sensing (CSS) can give further improvement in the detection reliability, the AOED algorithm is extended to cooperative sensing; in which multiple cognitive users collaborate to detect the primary transmission. The new combined approach (AOED and CSS) is shown to be more reliable detection than the individual detection scheme, where the hidden terminal problem can be mitigated. Furthermore, an optimal fusion strategy for hard-fusion based cognitive radio networks is presented, which optimises sensing performance. Thirdly, the need for denser deployment of base stations to satisfy the estimated high traffic demand in future wireless networks leads to a significant increase in energy consumption. Moreover, in large-scale cognitive radio networks some of cooperative devices may be located far away from the fusion centre, which causes an increase in the error rate of reporting channel, and thus deteriorating the performance of cooperative spectrum sensing. To overcome these problems, a new multi-hop cluster based cooperative spectrum sensing (MHCCSS) scheme is proposed, where only cluster heads are allowed to send their cluster results to the fusion centre via successive cluster heads, based on higher SNR of communication channel between cluster heads. Furthermore, in decentralised CSS as in cognitive radio Ad Hoc networks (CRAHNs), where there is no fusion centre, each cognitive user performs the local spectrum sensing and shares the sensing information with its neighbours and then makes its decision on the spectrum availability based on its own sensing information and the neighbours’ information. However, cooperation between cognitive users consumes significant energy due to heavy communications. In addition to this, each CR user has asynchronous sensing and transmission schedules which add new challenges in implementing CSS in CRAHNs. In this thesis, a new multi-hop cluster based CSS scheme has been proposed for CRAHNs, which can enhance the cooperative sensing performance and reduce the energy consumption compared with other conventional decentralised cooperative spectrum sensing modes

Design and Analysis of Opportunistic MAC Protocols for Cognitive Radio Wireless Networks

As more and more wireless applications/services emerge in the market, the already heavily crowded radio spectrum becomes much scarcer. Meanwhile, however,as it is reported in the recent literature, there is a large amount of radio spectrum that is under-utilized. This motivates the concept of cognitive radio wireless networks that allow the unlicensed secondary-users (SUs) to dynamically use the vacant radio spectrum which is not being used by the licensed primary-users (PUs). In this dissertation, we investigate protocol design for both the synchronous and asynchronous cognitive radio networks with emphasis on the medium access control (MAC) layer. We propose various spectrum sharing schemes, opportunistic packet scheduling schemes, and spectrum sensing schemes in the MAC and physical (PHY) layers for different types of cognitive radio networks, allowing the SUs to opportunistically utilize the licensed spectrum while confining the level of interference to the range the PUs can tolerate. First, we propose the cross-layer based multi-channel MAC protocol, which integrates the cooperative spectrum sensing at PHY layer and the interweave-based spectrum access at MAC layer, for the synchronous cognitive radio networks. Second, we propose the channel-hopping based single-transceiver MAC protocol for the hardware-constrained synchronous cognitive radio networks, under which the SUs can identify and exploit the vacant channels by dynamically switching across the licensed channels with their distinct channel-hopping sequences. Third, we propose the opportunistic multi-channel MAC protocol with the two-threshold sequential spectrum sensing algorithm for asynchronous cognitive radio networks. Fourth, by combining the interweave and underlay spectrum sharing modes, we propose the adaptive spectrum sharing scheme for code division multiple access (CDMA) based cognitive MAC in the uplink communications over the asynchronous cognitive radio networks, where the PUs may have different types of channel usage patterns. Finally, we develop a packet scheduling scheme for the PU MAC protocol in the context of time division multiple access (TDMA)-based cognitive radio wireless networks, which is designed to operate friendly towards the SUs in terms of the vacant-channel probability. We also develop various analytical models, including the Markov chain models, M=GY =1 queuing models, cross-layer optimization models, etc., to rigorously analyze the performance of our proposed MAC protocols in terms of aggregate throughput, access delay, and packet drop rate for both the saturation network case and non-saturation network case. In addition, we conducted extensive simulations to validate our analytical models and evaluate our proposed MAC protocols/schemes. Both the numerical and simulation results show that our proposed MAC protocols/schemes can significantly improve the spectrum utilization efficiency of wireless networks

Protocols for dynamic spectrum access in cognitive radio networks

Spectrum access protocols permit secondary users to transmit on frequency bands that are not being utilized by the primary owners. A cognitive radio that wishes to transmit in a band must first decide if the band is available (i.e., not being used by the owner) and then it must periodically re-evaluate the band\u27s availability once it begins transmitting in the band to ensure that a signal from a primary owner has not emerged. To accomplish these tasks, spectrum access protocols employ periodic sensing of the channel. Frequent sensing intervals are required to ensure that cognitive radios wishing to access the band are not disrupting transmissions by the owners of the band. Because spectrum sensing requires that radios cease transmission to observe the channel, the potential for throughput by the secondary users is reduced. A proposed enhancement to standard spectrum access protocols is presented that permits secondary users to monitor the frequency bands while communicating. This capability increases the amount of time that radios can transmit on the band and it decreases the amount of time required to detect the emergence of transmissions by a primary owner. Both improvements are obtained via a protocol that observes statistics obtained in the receiver of the cognitive radio during packet reception. The statistics are obtained with little or no additional hardware and do not require complicated channel measurements or pilot symbols. The proposed protocol for spectrum access is applicable to both single-link networks and multi-link cooperative networks

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

Cooperative Wideband Spectrum Sensing Based on Joint Sparsity

COOPERATIVE WIDEBAND SPECTRUM SENSING BASED ON JOINT SPARSITY By Ghazaleh Jowkar, Master of Science A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science at Virginia Commonwealth University Virginia Commonwealth University 2017 Major Director: Dr. Ruixin Niu, Associate Professor of Department of Electrical and Computer Engineering In this thesis, the problem of wideband spectrum sensing in cognitive radio (CR) networks using sub-Nyquist sampling and sparse signal processing techniques is investigated. To mitigate multi-path fading, it is assumed that a group of spatially dispersed SUs collaborate for wideband spectrum sensing, to determine whether or not a channel is occupied by a primary user (PU). Due to the underutilization of the spectrum by the PUs, the spectrum matrix has only a small number of non-zero rows. In existing state-of-the-art approaches, the spectrum sensing problem was solved using the low-rank matrix completion technique involving matrix nuclear-norm minimization. Motivated by the fact that the spectrum matrix is not only low-rank, but also sparse, a spectrum sensing approach is proposed based on minimizing a mixed-norm of the spectrum matrix instead of low-rank matrix completion to promote the joint sparsity among the column vectors of the spectrum matrix. Simulation results are obtained, which demonstrate that the proposed mixed-norm minimization approach outperforms the low-rank matrix completion based approach, in terms of the PU detection performance. Further we used mixed-norm minimization model in multi time frame detection. Simulation results shows that increasing the number of time frames will increase the detection performance, however, by increasing the number of time frames after a number of times the performance decrease dramatically