Analysis and Design of Multiple-Antenna Cognitive Radios with Multiple Primary User Signals

We consider multiple-antenna signal detection of primary user transmission signals by a secondary user receiver in cognitive radio networks. The optimal detector is analyzed for the scenario where the number of primary user signals is no less than the number of receive antennas at the secondary user. We first derive exact expressions for the moments of the generalized likelihood ratio test (GLRT) statistic, yielding approximations for the false alarm and detection probabilities. We then show that the normalized GLRT statistic converges in distribution to a Gaussian random variable when the number of antennas and observations grow large at the same rate. Further, using results from large random matrix theory, we derive expressions to compute the detection probability without explicit knowledge of the channel, and then particularize these expressions for two scenarios of practical interest: 1) a single primary user sending spatially multiplexed signals, and 2) multiple spatially distributed primary users. Our analytical results are finally used to obtain simple design rules for the signal detection threshold.Comment: Revised version (14 pages). Change in titl

Spectral and Energy Efficiency in Cognitive Radio Systems with Unslotted Primary Users and Sensing Uncertainty

This paper studies energy efficiency (EE) and average throughput maximization for cognitive radio systems in the presence of unslotted primary users. It is assumed that primary user activity follows an ON-OFF alternating renewal process. Secondary users first sense the channel possibly with errors in the form of miss detections and false alarms, and then start the data transmission only if no primary user activity is detected. The secondary user transmission is subject to constraints on collision duration ratio, which is defined as the ratio of average collision duration to transmission duration. In this setting, the optimal power control policy which maximizes the EE of the secondary users or maximizes the average throughput while satisfying a minimum required EE under average/peak transmit power and average interference power constraints are derived. Subsequently, low-complexity algorithms for jointly determining the optimal power level and frame duration are proposed. The impact of probabilities of detection and false alarm, transmit and interference power constraints on the EE, average throughput of the secondary users, optimal transmission power, and the collisions with primary user transmissions are evaluated. In addition, some important properties of the collision duration ratio are investigated. The tradeoff between the EE and average throughput under imperfect sensing decisions and different primary user traffic are further analyzed.Comment: This paper is accepted for publication in IEEE Transactions on Communication

Distributed Cooperative Sensing in Cognitive Radio Networks: An Overlapping Coalition Formation Approach

Cooperative spectrum sensing has been shown to yield a significant performance improvement in cognitive radio networks. In this paper, we consider distributed cooperative sensing (DCS) in which secondary users (SUs) exchange data with one another instead of reporting to a common fusion center. In most existing DCS algorithms, the SUs are grouped into disjoint cooperative groups or coalitions, and within each coalition the local sensing data is exchanged. However, these schemes do not account for the possibility that an SU can be involved in multiple cooperative coalitions thus forming overlapping coalitions. Here, we address this problem using novel techniques from a class of cooperative games, known as overlapping coalition formation games, and based on the game model, we propose a distributed DCS algorithm in which the SUs self-organize into a desirable network structure with overlapping coalitions. Simulation results show that the proposed overlapping algorithm yields significant performance improvements, decreasing the total error probability up to 25% in the Q_m+Q_f criterion, the missed detection probability up to 20% in the Q_m/Q_f criterion, the overhead up to 80%, and the total report number up to 10%, compared with the state-of-the-art non-overlapping algorithm

Spectrum Sensing Performance in Cognitive Radio Networks with Multiple Primary Users

Radio Spectrum sensing has been a topic of strong research in the last years due to its importance to Cognitive Radio (CR) systems. However, in Cognitive Radio Networks (CRNs) with multiple Primary Users (PUs), the Secondary Users (SUs) can often detect PUs that are located outside the sensing range, due to the level of the aggregated interference caused by that PUs. This effect, known as Spatial False Alarm (SFA), degrades the performance of CRNs, because it decreases the SUs’ medium access probability. This work characterizes the SFA effect in a CRN, identifying possible actions to attenuate it. Adopting Energy-based sensing (EBS) in each SU, this work starts to characterize the interference caused by multiple PUs located outside a desired sensing region. The interference formulation is then used to write the probabilities of detection and false alarm, and closed form expressions are presented and validated through simulation. The first remark to be made is that the SFA can be neglected, depending on the path loss factor and the number of samples collected by the energy detector to decide the spectrum’s occupancy state. However, it is shown that by increasing the number of samples needed to increase the sensing accuracy, the SUs may degrade their throughput, namely if SUs are equipped with a single radio that is sequentially used for sensing and transmission. Assuming this scenario, this paper ends by providing a bound for the maximum throughput achieved in a CRN with multiple active PUs and for a given level of PUs’ detection inside the SUs’ sensing region. The results presented in the paper show the impact of path loss and EBS parameterization on SUs’ throughput and are particularly useful to guide the design and parametrization of multi-hop CRNs, including future ad hoc cognitive radio networks considering multiple PUs