Abstract—We consider a cognitive radio system with N secondary user (SU) pairs and a pair of primary users (PU). The SU power allocation problem is formulated as a rate maximisation problem under PU and SU quality of service and SU peak power constraints. We show our problem formulation is a geometric program and can be solved with convex optimisation techniques. We examine the effect of PU transmissions in our formulations. Solutions for both low and high signal-to-interference-and-noise ratio (SINR) scenarios are provided. We show that including the PU rate in the optimisation problem leads to increased PU performance while not significantly degrading SU rate. Achievable rate cumulative distribution functions for various Rayleigh fading channels are produced.
Abstract—This paper presents a spectrum sensing algorithm for wideband interferers to be used within a cognitive radio. A two staged approach is proposed for the problem of wideband interferer detection. The first step requires that the frequency domain samples received are classified probabilistically amongst a number of possible statistical distributions, i.e. each sample is given a probability rating that reflects the likelihood that a specific sample was obtained using some specified distribution. The second stage of interferer detection uses these probabilities in a hidden Markov model to group highly likely samples into common interferer groups. This means that given a sample is highly likely to be an interferer, the surrounding frequency bins are also very likely to be an interferer since the interferers are wideband. Similarly, frequency bins contiguously surrounding a bin which is classified as noise only are more likely to be noise only bins as well. It is shown through simulation that this technique exhibits Receiver Operating Characteristics which are superior to other methods for wideband spectrum sensing.
Abstract—We consider a cognitive radio (CR) relay network consisting of a cognitive source, a cognitive destination and a number of cognitive relay nodes that share spectrum with a primary transmitter and receiver. Due to poor channel conditions, the cognitive source is unable to communicate directly with the cognitive destination and hence employs the cognitive relays for assistance. We assume that perfect channel state information (CSI) for all links is not available to the CR. Under the assumption of partial and imperfect CSI at the CR system, we propose new robust CR cooperative relay beamformers where either the total relay transmit power or the cognitive destination signal-to-interference-and-noise ratio (SINR) is optimised subject to a constraint on the primary receiver outage probability. We formulate the robust total relay power minimisation and the cognitive destination SINR maximisation optimisation problems as a convex second order cone program and a semidefinite program, respectively. Cumulative distribution functions of primary receiver and cognitive destination receiver SINR for Rayleigh fading channels are presented.
Abstract—This paper presents methods for enhancing blind spectrum sensing of wide-band signals using multiple antennas on a single cognitive receiver. Regulatory bodies in various countries have found that most radio spectrum is inefficiently utilized. Cognitive radio is a paradigm capable of utilizing bands assigned to licensed or primary users when they are not being used. A critical component of a functioning cognitive radio system is the spectrum sensing of the primary users. We present a hidden Markov model based approach to detecting wide-band signals with multiple antennas, contributing (i) simple means of combining signals across multiple antennas, namely pre-detection combining and post-detection combining, and (ii) a modified hidden Markov model algorithm to detect the interferers from the antenna-combined signals. The designs are characterized using both the dependence of missed detection and false alarm error rates on the Interference-to-Noise Ratio (INR) and receiver operator characteristics.
Abstract—The effect of narrowband interference on pilot symbol assisted detection and synchronization is discussed. It is shown both analytically and by computer simulation that pilot symbol detectors are particularly susceptible to narrowband interference. It is shown also that pilot symbol assisted frequency offset estimation is detrimentally affected by narrowband interference. The normalized least mean squares (N-LMS) adaptive noise cancellation algorithm, with only a small number of filter taps, is shown to perform well in suppressing narrowband interference in pilot symbol detectors. The combination of two-stage detection and the N-LMS algorithm is shown to be effective in producing interference-tolerant pilot symbol detection in OFDM systems.
This paper introduces a combined geographic and a Media Access Control (MAC) protocol for mesh, ad-hoc and cognitive networks. For mesh and ad-hoc networks, this paper examines the end-to-end (source to destination) link performance characteristics when supporting multimedia traffic. This paper also explains the cognitive network concept prior to analyzing cognitive network related results. The performance analysis was performed by a Monte Carlo simulator, the accuracy of which was verified by a Markov model analysis. An overlaid cell structure was considered for the Monte Carlo simulation where the terminals can be mobile within this environment. The system model includes Rice fading, log-normal shadowing and distance dependent pathloss. The system model also considers preferential channel access based on the capture effect. For mesh and ad-hoc networks, the proposed MAC protocol produced satisfactory performance characteristics in the presence of multimedia traffic. These results also show performance benefits of mesh networks over ad-hoc networks and how network density affects the network performance. Finally, the effect of primary users in cognitive networks is demonstrated.
Abstract—In this paper, we study the performance of quickest spectrum sensing when the received signal experiences various fading conditions, including the time-invariant, Rayleigh, Rician, Nakagami-m and the F channel. We prove that the power of the complex received signal is a sufficient statistic and derive the probability density function of the received signal amplitude for all of these fading cases. Simulation results reveal that the sensing performance degrades with the severity of the fading as well as the level of temporal correlation. We also consider mis-matched channel conditions and show that the average detection delay depends greatly on the channel but very little on the nature of the detector.
Abstract—We consider a cognitive radio (CR) network consisting of a secondary user transmitter (SU-Tx) equipped with multiple antennas and a secondary user receiver (SU-Rx) that share spectrum with multiple primary user transmitter (PUTx) and receiver (PU-Rx) pairs. We assume that the CR has a loose cooperation with the primary network and therefore, only partial channel state information of each of the PU-Tx to PU-Rx and SU-Tx to each PU-Rx links is available. Furthermore, we assume that the SU-Tx to SU-Rx link CSI is imperfect, with the channel error modelled as additive Gaussian noise. Under these assumptions, we propose a new statistically robust CR beamformer where the total SU-Tx transmit power is minimised subject to PU-Rx and SU-Rx outage probability constraints. We present expressions for PU-Rx and SU-Rx outage probabilities and formulate the robust beamformer optimisation problem as a convex semidefinite program (SDP). SU-Tx transmit power, PU-Rx signal-to-interference-and-noise ratio (SINR) and SU-Rx signal-to-noise (SNR) cumulative distribution functions (CDFs) are obtained through solution of our optimisation problem.
Abstract—Blind spectrum sensing using Bayesian sequential testing is examined to determine the effects of channel and channel model on detection performance. The theoretical framework is developed for Monte Carlo determination of type I and type II error probabilities for Bayesian sequential testing of Gaussian interference in a Rayleigh channel. It is shown that, while detection performance in a Rayleigh channel is degraded in comparison to that in a Gaussian channel, the choice of channel model has little impact on detection performance. This important result is extended to a previously-proposed method for dynamic spectrum sensing using pseudo two dimensional hidden Markov modeling, and new results given for Rayleigh channel performance.
Abstract-Cognitive radio technologies are being developed which allow heterogeneous systems to share spectrum access while minimizing interference to improve the overall efficiency of spectrum usage. Interference minimization requires cognitive radio receivers to be able to detect the presence of all other systems competing for spectrum usage, a process often termed "spectrum sensing". However, the performance of spectrum sensing algorithms depends on the statistics of a number of stochastic processes and even the most robust algorithms have finite probabilities of misclassification of interference, through either false detection or missed detection. This paper focuses on the impact of misclassification through missed detection of interference on the performance of shared spectrum systems, both primary and secondary. It is shown that interference misclassification in any part of the shared spectrum produces significant degradation on the performance of both primary and secondary systems. It is also shown that the incremental performance degradation due to interference from additional misclassified spectrum is significant for both primary and secondary systems.
Abstract—In this letter, we study quickest spectrum sensing for cognitive radios with multiple receive antennas in Gaussian and Rayleigh channels. We derive the probability density function for the fading case and analytically compute the upper bound and asymptotic worst-case detection delay for both of the cases. The extension into multiple antennas allows us to gain insights into the reduction in detection delay that multiple antennas can provide. Although sensing in a Rayleigh channel is more challenging, good sensing performance is still demonstrated. Index Terms—Cognitive radio, quickest spectrum sensing, CUSUM, multiple antennas, Gaussian channel, Rayleigh channel.
Abstract - The analytical bit error rate performance is described for a prototype broadband indoor communication system for multi-media applications. This system previously has been reported to achieve detection and synchronization using a pilot symbol. The bit error rate performance is compared, firstly, to the ideal bit error rate for this type of system and, secondly, to simulation results for the prototype system; both in an additive white Gaussian noise channel. A method is presented for extending these results to frequency flat multipath fading channels.
Abstract—Cognitive radios require accurate spectrum sensing decisions to minimize interference both to themselves and to primary and/or other secondary spectrum users. In dynamic spectrum environments, where interference may appear or disappear on any channel at any time instant, robust spectrum sensing is challenging particularly if only blind methods are available. Blind sensing methods for single spectrum sample vector operation are most sensitive at detecting changes in the interference environment, whereas sequential testing methods use more data to increase the reliability of detection decisions but are insensitive to spectrum dynamics. This paper reviews the Bayesian sequential testing approach and analyses the effect of parameter estimation on detection performance. A reduced complexity, two dimensional hidden Markov modeling method is proposed to improve the sensitivity of sequential testing to spectrum dynamics. The efficacy of this method is established by comparison with pure sequential testing and single spectrum sample vector detection.
Abstract—Cognitive radio technologies are being developed which allow heterogeneous systems to share spectrum access while minimizing interference to improve the overall efficiency of spectrum usage. Interference minimization requires cognitive radio receivers to be able to detect the presence of all other systems competing for spectrum usage, a process often termed “spectrum sensing”. This paper focuses on the kernel function of spectrum sensing: blind interference detection from a single, strictly time-limited, received data vector. Recent research has identified shortcomings in the operation of classical blind interference detection techniques such as energy detection and radiometry. This paper demonstrates that implicit interference characteristics can be exploited in a formal framework using hidden Markov modeling to produce a spectrum sensor with a receiver operating characteristic which is improved on that of energy detection and several other previously reported methods.
Abstract—In this paper, we consider a cognitive radio system with N secondary user (SU) pairs sharing a spectrum with a pair of primary users (PUs). The SU power allocation problem is formulated as a capacity maximization problem under PU and SU quality of service (QoS) and SU peak power constraints. We show that our problem formulation is a geometric program and can be solved with convex optimization techniques. We examine the effect of PU transmissions in our formulations. Solutions for both low- and high-signal-to-interference-and-noise ratio (SINR) scenarios are provided.We show that including PU capacity in the optimization problem in some circumstances leads to increased PU performance while not significantly degrading SU capacity. In a practical wireless communication system, accurate channel state information (CSI) is not often available; hence, we formulate power allocation problems with both perfect and imperfect CSI and analyze the performance loss incurred due to imperfect CSI. Furthermore, we present a novel method of detecting and removing infeasible SU QoS constraints from the SU power allocation problem that results in considerably improved SU performance. Cumulative distribution functions of capacity for various Rayleigh fading channels are presented.