Interference Spreading through Random Subcarrier Allocation Technique and Its Error Rate Performance in Cognitive Radio Networks

In this letter, we investigate the idea of interference spreading and its effect on bit error rate (BER) performance in a cognitive radio network (CRN). The interference spreading phenomenon is caused because of the random allocation of subcarriers in an orthogonal frequency division multiplexing (OFDM)-based CRN without any spectrum-sensing mechanism. The CRN assumed in this work is of underlay configuration, where the frequency bands are accessed concurrently by both primary users (PUs) and secondary users (SUs). With random allocation, subcarrier collisions occur among the carriers of primary users (PUs) and secondary users (SUs), leading to interference among subcarriers. This interference caused by subcarrier collisions spreads out across multiple subcarriers of PUs rather than on an individual PU, therefore avoiding high BER for an individual PU. Theoretical and simulated signal to interference and noise ratio (SINR) for collision and no-collision cases are validated for M-quadrature amplitude modulation (M-QAM) techniques. Similarly, theoretical BER performance expressions are found and compared for M-QAM modulation orders under Rayleigh fading channel conditions. The BER for different modulation orders of M-QAM are compared and the relationship of average BER with interference temperature is also explored further.

On the Performance of Random Cognitive mmWave Sensor Networks

This paper investigates the secrecy performance of a cognitive millimeter wave (mmWave) wiretap sensor network, where the secondary transmitter (SU-Tx) intends to communicate with a secondary sensor node under the interference temperature constraint of the primary sensor node. We consider that the random-location eavesdroppers may reside in the signal beam of the secondary network, so that confidential information can still be intercepted. Also, the interference to the primary network is one of the critical issues when the signal beam of the secondary network is aligned with the primary sensor node. Key features of mmWave networks, such as large number of antennas, variable propagation law and sensitivity to blockages, are taken into consideration. Moreover, an eavesdropper-exclusion sector guard zone around SU-Tx is introduced to improve the secrecy performance of the secondary network. By using stochastic geometry, closed-form expression for secrecy throughput (ST) achieved by the secondary sensor node is obtained to investigate secrecy performance. We also carry out the asymptotic analysis to facilitate the performance evaluation in the high transmit power region. Numerical results demonstrate that the interference temperature constraint of the primary sensor node enables us to balance secrecy performance of the secondary network, and provides interesting insights into how the system performance of the secondary network that is influenced by various system parameters: eavesdropper density, antenna gain and sector guard zone radius. Furthermore, blockages are beneficial to improve ST of the secondary sensor node under certain conditions.

Interference Temperature Measurements and Spectrum Occupancy Evaluation in the Context of Cognitive Radio

<span lang="EN-MY">This paper presents a refined radio spectrum measurement platform specifically designed for spectrum occupancy surveys in the context of Cognitive radio. Cognitive radio permits the opportunistic usage of licensed bands by unlicensed users without causing harmful interference to the licensed user. In this work, a study based on the measurement of the 800 MHz to 2.4 GHz frequency band at two different locations inside Universiti Teknologi Malaysia (UTM), Johor Bahru campus, Malaysia is presented. Two Tektronix RSA306B spectrum analyzer are set up to conduct simultaneous measurements at different locations for a 24 hours period. The analysis conducted in this work is based on the real spectrum data acquired from environment in the experimental set up. Busy and idle channels were identified. The channels subject to adjacent-channel interference were also identified, and the impact of the detection threshold used to detect channel activities was also discussed. The consistency of the observed channel occupation over a range of thresholds and a sudden drop has good characteristics in determining an appropriate threshold needed in order to avoid interference.</span>

Transmit precoding and Bayesian detection for cognitive radio networks with limited channel state information

Cognitive radio (CR) represents a recent direction for enabling coexistence among heterogeneous networks. It can be a potential solution for the problem of scarce spectrum available for wireless communication systems. The study here investigates the underlay and interweave paradigms for the coexistence of CR network of secondary users (SUs) with a primary network of primary users (PUs). Under underlay mode, both networks communicates concurrently using the same resources. With interweave, SU is able to communicate as long as (some) PUs are not active. Usually, underlay or interweave employs multiple antennas at SU to use the spectral resources better and manage the interference towards the primary network. Performance of the CR network under either paradigm depends largely on the amount and quality of channel state information (CSI) available about the different communication links. In practical systems, often CSI at SU has uncertainty since it is deviated from the true one or is not known at all. This uncertainty should be accounted when designing the precoding schemes for SU or otherwise the interference impact on primary networks would violate the quality of service (QoS) requirements for PUs. This dissertation considers two cases regarding to the availability of CSI, the first one is when CSI is imperfect and the second is when CSI is completely not known. For the underlay mode, we investigate two manifolds. The first one addresses the problem of maximizing the throughput of a multiple-input multiple-output (MIMO) SU when CSI of the interference link to PU is completely unknown or partially known. We study the achievable rates for SU under two different QoS requirements for the PU: the conventional interference temperature and leakage rate metrics. When CSI is unavailable, we develop an iterative adaptation algorithm that satisfies the QoS constraint through exploiting the side-information in the primary communication network. When CSI is inaccurate, we model the uncertainty deterministically such that the uncertainty error belongs to a convex compact set defined by the Schatten norm. We design the precoder by following the worst case formulation. We further investigate the relation between the unknown and the inaccurate CSI cases when using the interference temperature metric, and reveal that the performance of the latter is not necessarily better than the former. The second manifold assumes there is uncertainty in the SU intended link for communication as well as in the interference link from SU to PU. Similar to the first manifold, we follow the deterministic modelling using Schatten norm for the uncertainty and apply the worst case philosophy. For a given precoder matrix, we find the worst uncertainty error in the set that describes the uncertainty in each link. We further develop an iterative numerical algorithm for the precoder. Simpler solutions for the precoder and the uncertainty errors are derived under some special instances of the Schatten norm and certain requirement of transmission power. For the interweave mode, we assume there is no CSI available at SU and derive a Bayesian detector for the proposed binary hypothesis problem. For the null or noise model, we propose a conjugate prior for the unknown spatial covariance matrix. For the alternative or data model, we propose a new class of improper priors for the covariance matrix. We introduce the fractional Bayes factor (FBF) approach to enhance the detection capability of the Bayes factor. The developed FBF is compared with those using the conjugate priors for both hypotheses and generalized likelihood ratio test (GLRT), and it yields significant improvement.