Spectrum Sensing for Cognitive Radio Systems Through Primary User Activity Prediction

Traditional spectrum sensing techniques such as energy detection, for instance, can sense the spectrum only when the cognitive radio (CR) is is not in operation. This constraint is relaxed recently by some blind source separation techniques in which the CR can operate during spectrum sensing. The proposed method in this paper uses the fact that the primary spectrum usage is correlated across time and follows a predictable behavior. More precisely, we propose a new spectrum sensing method that can be trained over time to predict the primary user's activity and sense the spectrum even while the CR user is in operation. Performance achieved by the proposed method is compared to classical spectrum sensing methods. Simulation results provided in terms of receiver operating characteristic curves indicate that in addition to the interesting feature that the CR can transmit during spectrum sensing, the proposed method outperforms conventional spectrum sensing techniques

Robust Power and Subcarrier Allocation for OFDM-based Cognitive Radio Networks Considering Spectrum Sensing Uncertainties

‎In this paper‎, ‎we address power and subcarrier allocation for cooperative cognitive radio (CR) networks in the presence of spectrum sensing errors‎. ‎First‎, ‎we derive the mutual interference of primary and secondary networks affecting each other by taking into account spectrum sensing errors‎. ‎Then‎, ‎taking into account the interference constraint imposed by the cognitive network to the primary user and the power budget constraint of cognitive network‎, ‎we maximize the achievable data rates of secondary users‎. ‎Besides‎, ‎in a multi secondary user scenario‎, ‎we propose a suboptimal but low complexity power and subcarrier allocation algorithm to solve the formulated optimization problem‎. ‎Our numerical results indicate that the proposed power loading scheme increases the cognitive achievable data rates compared to classical power loading algorithms that do not consider spectrum sensing errors‎

A New Protocol for Cooperative Spectrum Sharing in Mobile Cognitive Radio Networks

To optimize the usage of limited spectrum resources, cognitive radio (CR) can be used as a viable solution. The main contribution of this article is to propose a new protocol to increase throughput of mobile cooperative CR networks (CRNs). The key challenge in a CRN is how the nodes cooperate to access the channel in order to maximize the CRN's throughput. To minimize unnecessary blocking of CR transmission, we propose a so-called new frequency-range MAC protocol (NFRMAC). The proposed method is in fact a novel channel assignment mechanism that exploits the dependence between signal's attenuation model, signal's frequency, communication range, and interference level. Compared .to the conventional methods, the proposed algorithm considers a more realistic model for the mobility pattern of CR nodes and also adaptively selects the maximal transmission range of each node over which reliable transmission is possible. Simulation results indicate that using NFRMAC leads to an increase of the total CRN's throughput by 6% and reduces the blocking rate by 10% compared to those of conventional methods

Improved Reception Schemes for Digital Video Broadcasting Based on Hierarchical Modulation

In this paper, we first provide an overview of Hierarchical Modulation (HM) along with the opportunities offered by this modulation in the context of the recent Digital Video Broadcasting standard for Satellite to Handheld devices (DVB-SH).With HM, the binary data is partitioned into a “high-priority” (HP) and a “low-priority” (LP) bit stream that are separately and independently encoded before being mapped on non-uniformly spaced constellation points. We will show that the robustness of the HP stream is obtained at the expense of performance degradation of the less protected LP stream with respect to a non-hierarchical modulation. To overcome this inherent drawback of HM, we propose two different reception schemes for improving the bit error rate performance of the less protected LP stream, while keeping the HP decoding performance unchanged. The important point is that in one of the proposed reception schemes, the performance improvement is achieved together with the reduction of the receiver’s complexity

A New Method For Increasing the Accuracy of EM-based Channel Estimation

It was recently shown that the detection performance can be significantly improved if the statistics of channel estimation errors are available and properly used at the receiver. Although in pilot-only channel estimation it is usually straightforward to characterize the statistics of channel estimation errors, this is not the case for the class of data-aided (semi-blind) channel estimation techniques. In this paper, we focus on the widely-used data-aided channel estimation techniques based on the expectation-maximization (EM) algorithm. This is achieved by a modified formulation of the EM algorithm which provides the receiver with the statistics of the estimation errors and properly using this additional information. Simulation results show that the proposed data-aided estimator outperform its classical counterparts in terms of accuracy, without requiring additional complexity at the receiver

Improved Design and Implementation of Variational Bayesian Iterative Receivers

It was recently shown that detection performance can be significantly improved if the statistics of channel estimation errors are available and properly used at the receiver. Although deriving the statistics of channel estimation errors is rather straightforward for pilot-only channel estimation methods, it is not the case for semi-blind receivers such as variational Bayesian (VB) receivers. We have shown in a recent contribution that by a modified formulation of the VB formalism, one can reduce the impact of channel uncertainty on the decoder performance. In this paper, we propose different practical VB receiver implementation techniques that lead to further performance improvement. The adequacy of the proposed receiver design compared to classically-used VB receivers is demonstrated by simulations for orthogonal frequency-division multiplexing (OFDM) systems

Smart primary user emulation in cognitive radio networks : Defence strategies against radio-aware attacks and robust spectrum sensing

Cognitive radio (CR), which provides dynamic spectrum access to combat spectrum scarcity, imposes some emerging threats to the network. One of the common threats in CR is primary user emulation (PUE) attack, in which some malicious users try to mimic primary signal and deceive CR users to prevent them from accessing the vacant frequency bands. In this paper, we propose a smart radio-aware PUE attacker that is equipped with spectrum sensing and consumes malicious resources in a way that causes more destruction on CR performance than always present PUE attackers. We first analyse and formulate the destructive effect such an attacker imposes to the CR network, and then, we derive robust cooperative spectrum sensing rules for energy detection spectrum sensing under PUE attacks. Moreover, using a weighting vector at fusion centre of the CRs, we propose a scheme to combat fake signals by maximising the average cognitive signal to interference plus noise ratio. We combine proposed method with two widely used energy detection scheme, Neyman-Pearson and minimum probability of error criterion. Numerical results show the superiority and robustness of our proposed method in the presence of smart attackers compared with conventional methods. In this paper, we analyze and formulate the destructive effect primary user emulation (PUE) attacker imposes to the CR network, and then, we derive robust cooperative spectrum sensing rules for energy detection spectrum sensing under PUE attacks. We propose a scheme to combat fake signals by maximizing the average cognitive signal to interference plus noise ratio. Numerical results show the superiority and robustness of our proposed method in the presence of smart attackers compared with conventional methods.</p

Achievable Outage Rates In Cognitive Radio Networks under Imperfect Spectrum Sensing

In this paper, we aim at deriving the outage rates achieved by the primary user due spectrum sensing in a cognitive radio network, that we call sensing-induced primary outage rates. To reach this goal, in the first step, instead of classical spectrum sensing techniques that evaluate sensing performance only based on correct detection of the presence of the primary user’s signal, we propose a modified framework that also takes into account the correct detection of the absence of primary user’s signal for spectrum sensing performance evaluation. In a second step, we derive the information rates achieved by the coexistence of a primary and a cognitive network. In the last step, assuming slow fading sensing channels, we derive the sensing-induced primary outage rates, i.e., outage rates achieved by the primary network in the presence of a CR with imperfect spectrum sensing, characterized by a given miss-detection probability. Numerical results show that the proposed spectrum sensing outperforms conventional spectrum sensing techniques in terms of primary signal outage rates and total achievable throughputs, without any increase in the cognitive radio complexity