Continuous sensing and transmission by secondary users (SUs) in cognitive radio (CR) allows efficient use of available spectrum. In this approach, the SU receiver continuously senses the spectrum while it transmits in the same frequency band. Leveraging this advantage, we study the performance of error vector magnitude (EVM) based detection to detect the reappearance of the primary user (PU) signal during ongoing SU data transmission. We exploit the pilot tones that are inherent to many OFDM based standards to measure the EVM. We consider two models of PU namely an unknown deterministic signal and a Gaussian random signal with additive white Gaussian noise (AWGN). We derive an analytical form of the probability density function (PDF) of the EVM based detector based on the exact representation of Chi-square distributions. We analyze the performance of our detector by deriving the type I (false positive) and type II (false negative) error probabilities. Simulation results show that the EVM based approach achieves better performance than energy detection.

In cognitive radio (CR) systems, secondary users (SUs) equipped with a single transceiver are unable to sense and transmit simultaneously. Due to this limitation, most of the models intended to describe spectrum sensing focus on pre‐transmission sensing and consider that primary users (PUs) only change their activity state in the beginning of each SU's operation cycle. This study characterises the more practical scenario which considers the reappearing PU during ongoing SU communication. The authors study a quickest detection scheme that uses an error vector magnitude (EVM) of the received signal. They consider two models of PUs namely an unknown deterministic signal and a Gaussian random signal with additive white Gaussian noise. The probability density function of the EVM test statistic is derived for both cases. The authors develop an exact quickest detection scheme by using a traditional cumulative sum (CUSUM) test. They show that CUSUM EVM outperforms CUSUM ED using theoretical analysis and numerical simulations.

We derive closed-form expressions to approximate the distribution of detection delay for a time-invariant cumulative sum detector. In addition, we derive approximations for the distribution of detection delay for the general case, which can be applied to any independent and identically distributed channel. We also employ random walk and Brownian motion theory to derive approximate expressions. The validity of these expressions is verified using simulations. We also approximate the probability of missed detection and investigate the probability of long detection delays via analysis and simulations. Numerical results show that different signal-to-noise ratio and detection delay conditions require different approaches to achieve good approximations of the detection delay distribution. Results also illustrate that the remarkably simple Brownian motion approach provides the best approximation for longer delays and the type of fading channel has very little impact on long detection delays.

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 optimized 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.

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 the CR has a very loose cooperation with the primary network and therefore, only partial channel state information is available. Under these assumptions, we propose a new statistically robust CR cooperative relay beamformer where either the total relay transmit power or the cognitive destination signal-to-interference-and-noise ratio (SINR) is optimised subject to primary receiver outage probability constraint. We formulate the robust total relay power and the cognitive destination SINR optimisation problems as a convex second order cone program and a convex feasibility problem, respectively, that provide near optimum results. We also present efficient iterative algorithms that provide the optimum results.

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.

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.

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.

The effect of narrowband interference on OFDM systems is considered, with particular regard to the receiver post-detection bit error rate performance. It is shown both by analysis and by computer simulation that the ensemble average bit error rate is severely affected by narrowband interference and that particular values of interferer carrier frequency and phase can produce bit error rates significantly higher than the ensemble average. An interference suppression technique based on excision (notch) filtering is proposed and is shown by computer simulation to improve ensemble average bit error rates to about 0.001 for BPSK modulated OFDM with signal-to-interference ratios as low as -30 dB

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.

Future wireless local area networks (WLAN) will use orthogonal frequency division multiplexing (OFDM). The analytical bit error rate performance is described for a prototype broadband indoor communication system for multimedia 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.

The design of a pilot symbol for orthogonal frequency-division multiplexing packet detection and synchronization is presented. Algorithms are described for packet detection and for synchronization using maximum likelihood estimation of channel frequency offset, phase offset for coherent detection, and subsample timing offset. The efficacy of the detection and synchronization algorithms is demonstrated experimentally.

A performance analysis of algorithms for maximum likelihood estimation of channel parameters for orthogonal frequency-division multiplexing packet detection and synchronization is presented. The detection and synchronization algorithms, which are based on the use of a pilot symbol, are described in Coulson (2001). The performance analyses concentrate on operation in additive white Gaussian noise channels, and the accuracy of these analyses are demonstrated using experimental and simulation data. Methods to extend these analyses to frequency flat multipath fading channels are presented.

Empirical justifications for the lognormal, Rayleigh and Suzuki (1977) probability density functions in multipath fading channels are examined by quantifying the rates of convergence of the central limit theorem (CLT) for the addition and multiplication of random variables. The accuracy of modeling the distribution of rays which experience multiple reflections/diffractions between transmitter and receiver as lognormal is quantified. In addition, it is shown that the vector sum of lognormal rays, such as in a narrow-band signal envelope, may best be approximated as being either Rayleigh, lognormal or Suzuki distributed depending on the fading channel conditions. These conditions are defined statistically.

A signal combination technique, based on the spectral replication property of sampling, is presented. The technique uses second-order bandpass sampling to provide some phase control over the component signals. Although the phase control is not independent between the signals and is further constrained by inherent amplitude scaling, quasi-independent control can be achieved. The performance of the combination technique is established for two applications. These applications are diversity antenna combination and demodulation of slow frequency-hopping spread spectrum.>