Zhijin Qin

Wideband Spectrum Sensing on Real-Time Signals at Sub-Nyquist Sampling Rates in Single and Cooperative Multiple Nodes

This paper presents two new algorithms for wideband spectrum sensing at sub-Nyquist sampling rates, for both single nodes and cooperative multiple nodes. In single-node spectrum sensing, a two-phase spectrum sensing algorithm based on compressive sensing is proposed to reduce the computational complexity and improve the robustness at secondary users (SUs). In the cooperative multiple nodes case, the signals received at SUs exhibit a sparsity property that yields a low-rank matrix of compressed measurements at the fusion center. This therefore leads to a two-phase cooperative spectrum sensing algorithm for cooperative multiple SUs based on low-rank matrix completion. In addition, the two proposed spectrum sensing algorithms are evaluated on the TV white space (TVWS), in which pioneering work aimed at enabling dynamic spectrum access into practice has been promoted by both the Federal Communications Commission and the U.K. Office of Communications. The proposed algorithms are tested on the real-time signals after they have been validated by the simulated signals in TVWS. The numerical results show that our proposed algorithms are more robust to channel noise and have lower computational complexity than the state-of-the-art algorithms.

Enhancing the Physical Layer Security of Non-Orthogonal Multiple Access in Large-Scale Networks

This paper investigates the physical layer security of non-orthogonal multiple access (NOMA) in large-scale networks with invoking stochastic geometry. Both single-antenna and multiple-antenna aided transmission scenarios are considered, where the base station (BS) communicates with randomly distributed NOMA users. In the single-antenna scenario, we adopt a protected zone around the BS to establish an eavesdropper-exclusion area with the aid of careful channel ordering of the NOMA users. In the multiple-antenna scenario, artificial noise is generated at the BS for further improving the security of a beamforming-aided system. In order to characterize the secrecy performance, we derive new exact expressions of the security outage probability for both single-antenna and multiple-antenna aided scenarios. For the single-antenna scenario, we perform secrecy diversity order analysis of the selected user pair. The analytical results derived demonstrate that the secrecy diversity order is determined by the specific user having the worse channel condition among the selected user pair. For the multiple-antenna scenario, we derive the asymptotic secrecy outage probability, when the number of transmit antennas tends to infinity. Monte Carlo simulations are provided for verifying the analytical results derived and to show that: 1) the security performance of the NOMA networks can be improved by invoking the protected zone and by generating artificial noise at the BS and 2) the asymptotic secrecy outage probability is close to the exact secrecy outage probability.

Data-Assisted Low Complexity Compressive Spectrum Sensing on Real-Time Signals Under Sub-Nyquist Rate

In this paper, we present a novel hybrid framework combining compressive spectrum sensing with geo-location database to find spectrum holes in a decentralized cognitive radio. In the hybrid framework, a geo-location database algorithm is proposed to be stored locally at secondary users (SUs) to remove the extra transmission link to a centralized remote geo-location database. Specifically, by utilizing the output of the locally stored geo-location database algorithm, a data-assisted noniteratively reweighted least squares (DNRLS)-based compressive spectrum sensing algorithm is proposed to improve detection performance under sub-Nyquist sampling rates for wideband spectrum sensing, and to reduce the computational complexity of signal recovery. In addition, an efficient method for the calculation of maximum allowable equivalent isotropic radiated power in TV white space (TVWS) is also designed to further support SUs. The convergence and complexity of the proposed DNRLS algorithm are analyzed theoretically. Furthermore, the proposed framework is pioneered on real-time “from air” signals and data after having been validated by simulated signals and data in TVWS.

To white space or not to White Space: That is the trial within the Ofcom TV White Spaces pilot

TV White Space (TVWS) has taken a big step forward with the UK regulator Ofcom initiating a pilot of the technology in the UK, based on rules for White Space Devices (WSDs) standardized and harmonized at the European level by ETSI. This paper reports on a subset of the work undertaken by our large-scale trial within the Ofcom Pilot, investigating what is achievable in TVWS in terms of availability and capacity, and strongly focusing on the potential to aggregate white space resources. Moreover, this paper provides some experimental results and observations from our trial, particularly around issues such as performance testing and assessment of appropriate scenarios for TVWS deployments. Some of the key observations in this paper, among numerous others, include: (i) In the UK, it seems likely that TVWS has most performance/benefit potential in below-rooftop receiver and indoor/underground deployments. For availability and capacity analyses, we particularly define and assess TVWS scenarios that we term as “mobile broadband downlink” and “indoor wireless local-area networking” based on this realization. We further demonstrate the strength of TVWS for indoor communications through a range of challenging experiments inside the Strand Campus of Kings College London. (ii) There is ample TVWS available in much of the UK and particularly in the London area, although this is affected greatly by the scenario that is considered and can be very highly variable. The mobile broadband downlink scenario is particularly affected by availability reduction and variability outside of the London area. Impressive capacities can be achieved by optimal aggregation in TVWS. Achievable area capacity in TVWS is high. (iii) In a number of cases, and particularly under some aggregation scenarios, subsets or indeed all WSD spectrum mask classes give similar performance. (iv) A worst case 700 MHz spectrum reassignment for ITU Region 1 in WRC 2015 could significantly affect availability/capacity in some TVWS usage scenarios, for lower quality spectrum mask class WSDs.

Physical layer security for 5G non-orthogonal multiple access in large-scale networks

In this paper, the physical layer security of applying non-orthogonal multiple access (NOMA) in large-scale networks is investigated. In the considered scenario, both the NOMA users and eavesdroppers are spatially randomly deployed. A protected zone around the source node is adopted to enhance the security of a random network. In order to characterize the secrecy performance of the considered scenario, new exact and asymptotic expressions for the security outage probability are derived. These analytical results demonstrate that the secrecy diversity order is m, which is determined by the user with poor channel condition. Monte Carlo simulations are provided to verify the derived analytical results. Furthermore, it is also confirmed that the secure performance of the NOMA networks can be improved by either enlarging the scope of the protected zone or reducing the scope of the user zone.

Compressive spectrum sensing augmented by geo-location database

In cognitive radio (CR), white space devices (WSDs) need to have the knowledge of spectrum occupancy in TV white space (TVWS) before dynamic access. There are two common schemes proposed to achieve this: 1) geo-location database and 2) spectrum sensing. In geo-location database, calculating digital terrestrial television (DTT) location probability and maximum permitted power in each channel in an efficient way becomes important as the database is supposed to give a quick response once a request comes. Spectrum sensing is a scheme which can provide a more reliable and real-time results for spectrum occupancy. However, the high sampling rate is a big challenge in spectrum sensing for power limited WSDs. In this paper, we proposed to combine the location probability based geo-location database with compressive sensing (CS) based spectrum sensing to achieve sub-Nyquist sampling rates for WSDs. The history data from geo-location database is utilized to support the signal recovery for the spectrum sensing. In addition, a new method to calculate DTT location probability efficiently is proposed. Theoretical analysis of the proposed algorithm are tested in TVWS and it shows that performance of the proposed algorithm outperforms the traditional algorithm.

Scalable and Reliable IoT Enabled by Dynamic Spectrum Management for M2M in LTE-A

To underpin the predicted growth of the Internet of Things (IoT), a highly scalable, reliable and available connectivity technology will be required. Whilst numerous technologies are available today, the industry trend suggests that cellular systems will play a central role in ensuring IoT connectivity globally. With spectrum generally a bottleneck for 3GPP technologies, TV white space (TVWS) approaches are a very promising means to handle the billions of connected devices in a highly flexible, reliable and scalable way. To this end, we propose a cognitive radio enabled TD-LET test-bed to realize the dynamic spectrum management over TVWS. In order to reduce the data acquisition and improve the detection performance, we propose a hybrid framework for the dynamic spectrum management of machine-to-machine networks. In the proposed framework, compressed sensing is implemented with the aim to reduce the sampling rates for wideband spectrum sensing. A noniterative reweighed compressive spectrum sensing algorithm is proposed with the weights being constructed by data from geolocation databases. Finally, the proposed hybrid framework is tested by means of simulated as well as real-world data.

Wireless Powered Cognitive Radio Networks With Compressive Sensing and Matrix Completion

In this paper, we consider cognitive radio networks in which energy constrained secondary users (SUs) can harvest energy from the randomly deployed power beacons. A new frame structure is proposed for the considered networks. In the considered network, a wireless power transfer model is proposed, and the closed-form expressions for the power outage probability are derived. In addition, in order to reduce the energy consumption at SUs, sub-Nyquist sampling are performed at SUs. Subsequently, compressive sensing and matrix completion techniques are invoked to recover the original signals at the fusion center by utilizing the sparsity property of spectral signals. Throughput optimizations of the secondary networks are formulated into two linear constrained problems, which aim to maximize the throughput of a single SU and the whole cooperative network, respectively. Three methods are provided to obtain the maximal throughput of secondary networks by optimizing the time slots allocation and the transmit power. Simulation results show that the maximum throughput can be improved by implementing compressive spectrum sensing in the proposed frame structure design.

Some Initial Results and Observations from a Series of Trials within the Ofcom TV White Spaces Pilot

TV White Spaces (TVWS) technology allows wireless devices to opportunistically use locally-available TV channels enabled by a geolocation database. The UK regulator Ofcom has initiated a pilot of TVWS technology in the UK. This paper concerns a large- scale series of trials under that pilot. The purposes are to test aspects of white space technology, including the white space device and geolocation database interactions, the validity of the channel availability/powers calculations by the database and associated interference effects on primary services, and the performances of the white space devices, among others. An additional key purpose is to perform research investigations such as on aggregation of TVWS resources with conventional resources and also aggregation solely within TVWS, secondary coexistence issues and means to mitigate such issues, and primary coexistence issues under challenging deployment geometries, among others. This paper provides an update on the trials, giving an overview of their objectives and characteristics, some aspects that have been covered, and some early results and observations.

Efficient compressive spectrum sensing algorithm for M2M devices

Spectrum used for Machine-to-Machine (M2M) communications should be as cheap as possible or even free in order to connect billions of devices. Recently, both UK and US regulators have conducted trails and pilots to release the UHF TV spectrum for secondary licence-exempt applications. However, it is a very challenging task to implement wideband spectrum sensing in compact and low power M2M devices as high sampling rates are very expensive and difficult to achieve. In recent years, compressive sensing (CS) technique makes fast wideband spectrum sensing possible by taking samples at sub-Nyquist sampling rates. In this paper, we propose a two-step CS based spectrum sensing algorithm. In the first step, the CS is implemented in an SU and only part of the spectrum of interest is supposed to be sensed by an SU in each sensing period to reduce the complexity in the signal recovery process. In the second step, a denoising algorithm is proposed to improve the detection performance of spectrum sensing. The proposed two-step CS based spectrum sensing is compared with the traditional scheme and the theoretical curves.