Bassem Zayen

Blind Spectrum Sensing for Cognitive Radio Based on Signal Space Dimension Estimation

Based on information theoretic tools, a new spectrum sensing method is proposed in this paper to detect vacant sub-bands in the radio spectrum1. Specifically, based on the subspace analysis of the received signal, we present a new method to detect the signal presence in a blind way. We have shown that the analysis of signal dimension can assist blind spectrum sensing procedure. Indeed, we have shown that the slope change, from positive to negative trend, of the signal space dimension curve is representative of the transition from a vacant band to an occupied band (and vice versa). In fact, the number of significant eigenvalues is determined by the value that minimizes the Akaikes Information Criterion (AIC) and is directly related to the presence/absance of data in the signal. The validation of this new method is based on experimental measurements captured by Eurecom RF Agile Platform operating from 200 MHz to 7.5 GHz. Simulations show good results in terms of spectrum holes detection.

Blind Spectrum Sensing for Cognitive Radio Based on Model Selection

Cognitive radio devices will be able to seek and dynamically use frequency bands for network access. This will be done by autonomous detection of vacant sub-bands in the radio spectrum. In this paper, we propose a new method for blind detection of vacant sub-bands over the spectrum band. The proposed method exploits model selection tools like Akaike information criterion (AIC) and Akaike weights to sense holes in the spectrum band. Specifically, we assume that the noise of the radio spectrum band can still be adequately modeled using Gaussian distribution. We then compute and analyze Akaike weights in order to decide if the distribution of the received signal fits the noise distribution or not. Our theoretical result are validated using experimental measurements captured by Eurecom RF Agile Platform. Simulations show promising performance results of the proposed technique in terms of sensing vacant sub-bands in the spectrum.

Design and implementation of spatial interweave LTE-TDD cognitive radio communication on an experimental platform

Cognitive radio, which enables smart use of wireless resources, is a key ingredient to achieve high spectral efficiency. LTE, the latest evolution of cellular standards, is widely adopted and also targets high spectral efficiency. Hence, to enable wide adoption of cognitive radio, using LTE as the physical layer is a natural choice. Targeting a real-time implementation of LTEbased cognitive radio, we focus on spatial interweave cognitive radio, in which a secondary user uses an antenna array to perform null-beamforming in the primary users direction, hence reusing the spectrum spatially. To allow this, without any help from the primary system, we use the time-division duplex mode and take advantage of the channel reciprocity. However, this reciprocity is jeopardized by the mismatch between the RF front-ends. Hence, we design a calibration protocol to restore it. A key contribution is that this cognitive system calibration does not require cooperation from the primary user. The whole system is implemented and evaluated on EURECOMs experimental OpenAirInterface platform. Performance results are presented, showing the feasibility of spatial interweave cognitive radio on a real-time platform.

Spectrum sensing for cognitive radio exploiting spectrum discontinuities detection

This article presents a spectrum sensing algorithm for wideband cognitive radio exploiting sensed spectrum discontinuity properties. Some work has already been investigated by wavelet approach by Giannakis et al., but in this article we investigate an algebraic framework in order to model spectrum discontinuities. The information derived at the level of these irregularities will be exploited in order to derive a spectrum sensing algorithm. The numerical simulation show satisfying results in terms of detection performance and receiver operating characteristics curves as the detector takes into account noise annihilation in its inner structure.

Resource allocation for cognitive radio networks with a beamforming user selection strategy

In this paper we address the problem of resource allocation in the context of cognitive radio networks (CRN). With the deployment of K antennas at the cognitive base station (CBS), an efficient transmit beamforming technique combined with user selection is proposed to maximize the uplink throughput and satisfy the signal-to-noise and interference ratio (SNIR) constraint, as well as to limit interference to the primary user (PU). In the proposed user selection algorithm, secondary users (SUs) are first pre-selected so as to maximize the per-user sum capacity subject to minimize the mutual interference. Then, the PU verifies the outage probability constraint and a number of SUs are selected from those pre-selected SUs. Simulation results show that our proposed method exhibits a significant number of cognitive users able to transmit while minimizing interference to guarantee QoS for the PU. We also compare the results obtained by the proposed method to those obtained using a binary power allocation method. The reported results demonstrate the efficiency of the proposed technique to maximize the SU rate while maintaining a QoS to a PU, and its superiority to the binary power allocation.

Utility/pricing-based resource allocation strategy for cognitive radio systems

In this paper1, we propose a resource allocation scheme based on a utility/pricing strategy with the objective to maximize a defined utility function subject to minimize the mutual interference caused by secondary users (SUs) with protection for primary users (PUs). Specifically, we formulate a utility function to reflect the needs of PUs by verifying the outage probability constraint, and the per-user capacity by satisfying the signal-to-noise and interference ratio (SNIR) constraint, as well as to limit interference to PUs. Furthermore, the existence of the Nash equilibrium of the proposed game is established, as well as its uniqueness under some sufficient conditions. Theoretical and simulation results based on a realistic network setting, and a comparison with a previously published binary power allocation method will be provided in this paper. The reported results demonstrate the efficiency of the proposed technique in terms of cognitive radio network (CRN) deployment while maintaining quality-of-service (QoS) for the primary system, and its superiority to the binary power allocation.

Application of smoothed estimators in spectrum sensing technique based on model selection

In cognitive radio networks, secondary user (SU) does not have rights to transmit when the primary user (PU) band is occupied, thats why a sensing technique must be done. Recently, a new blind spectrum sensing technique based on distribution analysis was developed for sensing the spectrum holes in the PU band. Specifically, assuming that the noise of the radio spectrum band can still be adequately modeled using Gaussian distribution, this detector decide if the distribution of the received signal fits the noise distribution or not. This technique is computationally simple and fast. In this paper1, we investigate the effect of applying smoothed estimators for this spectrum sensing technique. We will show that the application of smoothed periodograms offers good performances and keeps a reasonable complexity. Simulations results and performances evaluation presented in this paper are based on experimental measurements captured by Eurécom RF Agile Platform.

Performance comparison for low complexity blind sensing techniques in cognitive radio systems

In this paper1, we will provide a straightforward classification of some spectrum sensing strategies derived at Eurecom attempting to show the diversity and advantages of these spectrum sensing techniques. Specifically, two low complexity blind sensing algorithms were developed to detect spectrum holes in the primary users bands: the distribution analysis detector (DAD) and the algebraic detector (AD), which are compared with the energy detector (ED) as reference algorithm. For performance evaluation we have chosen to thoroughly investigate the DVB-T primary user system. Simulation results show that the two proposed detectors offer high performances and detect primary users presence even at very low SNR with comparable complexity to ED.

Software implementation of spatial interweave cognitive radio communication using OpenAirInterface platform

We present in this paper a software implementation of a cognitive radio (CR) communication based on long term evolution-time division duplex (LTE-TDD) channel reciprocity. We study the problem of calibration and beamforming design for a CR system in which a multiple-input single-output (MISO) secondary link, wants to opportunistically communicate without harming the primary SISO system. Specifically, we evaluate the CR communication through the EURECOMs experimental OpenAirInterface (OAI) software platform. We will show that it is feasible to restore the reciprocity after calibration in a non reciprocal channel, and provide an overview of challenges in the channel estimation for real conditions.

Dimension estimation-based spectrum sensing for cognitive radio

In this article, we will derive closed-form expressions of false alarm probabilities for a given threshold for the dimension estimation-based detector (DED) using Akaike information criterion (AIC) and the minimum description length (MDL) criterion. Specifically, the DED algorithm will be formulated as a binary hypothesis test using AIC and MDL curves. Based on the proposed statistic test, we will express the probability of false alarm of the DED algorithm for a fixed threshold using the cumulative density function for the distribution of Tracy-Widom of order two. The derived analytical decision thresholds are verified with Monte-Carlo simulations and a comparison between simulation and analytical results to confirm the theoretical results are presented. These results confirm the very good match between simulation and theoretic results.