Alan J. Coulson

A statistical basis for lognormal shadowing effects in multipath fading channels

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.

Narrowband interference in pilot symbol assisted OFDM systems

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.

Bit error rate performance of OFDM in narrowband interference with excision filtering

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

Extension of Quickest Spectrum Sensing to Multiple Antennas and Rayleigh Channels

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.

Do wireless data signals exhibit spectral autocorrelation

Signal spectra of wireless data systems are well known to be uncorrelated provided the communicated data sequence itself is white. However, multiplicative processes in wireless transmission systems and multipath fading channels produce spectral correlation. This paper shows that, where spectrum sensing opportunities are short in duration, the sample vector spectrum covariance matrix typically remains purely diagonal. It is also shown that signal spectra may be somewhat correlated in instances where the channel Doppler spread is severe, or where the measurement system has resolution bandwidth smaller than that of the wireless data system.

Robust Cognitive Radio Cooperative Beamforming

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.

Interference management in cognitive radio systems — A convex optimisation approach

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.

Interference Management in Cognitive Radio Systems With Feasibility Detection

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.

Power allocation in underlay cognitive radio systems with feasibility detection

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 capacity maximisation problem under PU and SU quality of service and SU peak power constraints. The problem is formulated as a geometric program, solved for both low- and high- signal-to-interference-and-noise ratio (SINR) regimes. We present a novel method of detecting and removing infeasible SU quality of service constraints from the SU power allocation problem that results in considerably improved SU performance. Capacity cumulative distribution functions for Rayleigh fading channels are produced.

Blind Spectrum Sensing Using Bayesian Sequential Testing with Dynamic Update

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.