Managing trust in mobile networks necessitates dealing with uncertainty, resulting from incomplete, duplicate or conflicting evidence. In this work, possibility theory is used to deal with uncertainty, and a trust model is developed that includes the network nodes' integrity, their competency and that of the connections among them. Evidence obtained by direct observation (`passive') is integrated with that solicited from other nodes (`active') to generate possibility distributions, or trust profiles, that can be combined, updated and discounted. Simulations of mobile ad hoc networks show that the inclusion of these trust profiles in routing decisions conserves network resources and limits data exposure by directing packets over reliable links through uncompromised nodes. Possibility theory enables the information gain provided by different forms of evidence to be evaluated, and this is used to explore the benefits of different sources of active trust evidence. It is seen that passive evidence is not sufficient to maintain trust profiles with low uncertainty, and that active trust evidence obtained by authentication requests provides higher informational value than that received using reputation solicitation.

Secrecy rate achievability in three-node amplify-and-forward cooperative systems at the presence of passive eavesdroppers without location information is statistically analyzed and optimized. First, the effective vulnerability area, the area in which no secrecy rate is achievable when an eavesdropper resides in that area, is introduced as the performance metric to measure the security of the cooperative system. Then, it is shown analytically that the best location of the relay to minimize the effective vulnerability region is on the source-destination crossing line. In addition, it is proved that the optimum relay with the best location and power allocation is located on the line segment bounded by the source and destination. Exact and some special closed-form expressions for the probability of secrecy rate achievability are obtained for the Rayleigh fading environment. Using this, the impact of the location and the relay power on the effective vulnerability area are analyzed and the best cases minimizing this area are numerically computed. It is shown that the effective vulnerability area can be reduced more than 50% in comparison with the case where no relay is used if the optimum relay location and the optimum relay power allocation are adopted.

The performance of mobile multiple‐input–multiple‐output (MIMO) systems is determined both by the instantaneous channel characteristics and by the rate of change of those characteristics. The local environment and operating frequency affect the spatial channel response, which impacts the ability of the system to sustain data throughput, while the dynamics of the channel response impact the accuracy of the available channel state information, limiting the supportable packet length. Measured MIMO data from two frequencies in the UHF band are characterised and used to investigate the dependence of system performance on the changing spatial channel responses. It is demonstrated that to maximise average throughput, taking into account retransmissions because of packet failures, a trade‐off is required among the data rate, training overhead and packet length, which depends on both the operating frequency and the local environment. This work emphasises the importance both of adaptation in MIMO communication systems and of considering realistic channel conditions in their design and evaluation.

This paper presents two polynomial-complexity techniques for assigning Gray-like binary labels to arbitrary Grassmannian constellations. In the first technique, the constellation of interest, C, is matched directly to an auxiliary constellation that can be readily Gray labelled. The optimal matching in this technique can be obtained efficiently, but its application is limited to cases in which an auxiliary constellation with a geometric structure that resembles that of C can be identified. In the second technique no auxiliary constellation is required and the labels are generated by matching the distance spectrum of C with that of a hypothetical constellation that is assumed to be perfectly Gray labelled. Optimal matching in this case is computationally prohibitive. Instead, an efficient suboptimal matching algorithm is proposed. When compared with several existing schemes, the proposed labellings provide better performance in both uncoded and BICM-based non-coherent MIMO systems with iterative demapping and decoding (IDD). Furthermore, with the proposed labels, the Grassmannian-based BICM-IDD scheme performs better than a training-based counterpart that employs the Golden code and optimal demapping.

The sensitivity of MIMO error performance to imperfect receiver channel state information is examined. Measurements made at three different UHF frequencies are used to show the effect of parameters such as training and frame lengths on error performance. The results show that the amount of training directly influences the supportable symbol rate and that the level of degradation in performance due to delay is highly dependent on frame length, frequency and channel geometry.

In this paper, we consider cooperative ad hoc networks and develop an analytical model to study the performance of reliable relaying schemes. In particular, we develop expressions for throughput rate and spectral efficiency for cooperating radios in a fading environment. The numerical results indicate a performance conflict between throughput rate and spectral efficiency, which depends on the underlying relaying schemes, channel quality and number of relays.

Cognitive radios must be able to form collaborative wireless network clusters in dynamically changing environments to achieve such desired objectives as interference resilience and low communications overhead. In this work, we explore the affinity propagation (AP) message-passing technique to efficiently group nodes in an ad hoc cognitive radio network (CRN). With the proposed approach, nodes exchange local messages with their immediate neighbours until a high quality set of clusterheads and a corresponding cluster structure emerges. The messages are calculated based on measures of similarity between the network nodes, which are selected based on application requirements and the objective of the grouping process. As an initial application, we focus on finding a small dominating set of a CRN with the aim of reducing the number of nodes that participate in key network functions such as resource management and routing table maintenance. To demonstrate the merits of the proposed clustering approach, the AP technique is evaluated on randomly generated open spectrum access network scenarios. The simulation results demonstrate that the proposed technique provides a smaller number of clusters than methods based on approximating a minimum size dominating set of the corresponding ad hoc network graphs.

In this paper we describe a series of urban measurements designed to characterize the MIMO channel when antenna arrays with dual-polarized elements are placed on the sides of the mobile receiver. It is seen that the received signal power is highly dependent on the physical environment local to the receiver and on the position of the vehicular mounted array elements relative to the transmitter. These factors, combined with the channel's propagation characteristics, result in a spatial power imbalance across the arrays as well as cross polarization discrimination (XPD). When the spatial array power imbalance (API) exceeds the XPD polarization diversity can be exploited to improve the system performance. However, when the XPD is greater than the API spatial diversity results in improved performance.

Accurate and sparse representation of a moderately fast fading channel using bases functions is achievable when both channel and bases bands align. If a mismatch exists, usually a larger number of bases functions is needed to achieve the same accuracy. In this paper, we propose a novel approach for channel estimation based on frames, which preserves sparsity and improves estimation accuracy. Members of the frame are formed by modulating and varying the band-width of discrete prolate spheroidal sequences (DPSS) in order to reflect various scattering scenarios. To achieve the sparsity of the proposed representation, a matching pursuit approach is employed. The estimation accuracy of the scheme is evaluated and compared with the accuracy of a Slepian basis expansion estimator based on DPSS for a variety of mobile channel parameters. The results clearly indicate that for the same number of atoms, a significantly higher estimation accuracy is achievable with the proposed scheme when compared to the DPSS estimator.

In order for MIMO systems to function in real applications, factors such as realistic channel responses and frame structures must be incorporated into their design. Limited feedback precoding schemes have recently been introduced to address limitations with feedback overhead. The performance of two techniques is compared when subjected to delays typical in systems employing data frames using channel responses measured in an urban microcell. The results show that feedback approaches based on matching transmission to specific channel state information are less robust to delays in channel information than methods which feed back symbol rate information.

The Ricean K-factor is a practical channel quality measure in many wireless communication applications as it exhibits a fast estimation convergence compared with the explicit estimation of performance metrics such as error rates. Recently, it has been shown that estimation of the K-factor can be improved relative to envelope-based detectors through the use of complex (I/Q) channel observations. In this paper, an analysis of the maximum likelihood estimator of the K-factor from I/Q samples is presented, which illustrates the bias of previous estimators. An improved estimator is then proposed, which has superior bias and efficiency for short data records. For mobile applications, a reliable estimator of the Doppler shift of the specular component is incorporated. Simulation results for a range of channel conditions illustrate that the proposed estimator outperforms prior techniques, and provide insight into the record lengths required to achieve a desired estimation accuracy.

MIMO system design for real applications requires that factors such as channel estimation errors, feedback quantisation and realistic channel responses be taken into account. Limited feedback precoding has been introduced to address the feedback overhead; it is a quantised approximation to equal-power eigenbeamforming. The performance of this technique is evaluated using channel responses obtained from a typical urban microcell. The impact of inaccurate channel state information is considered, in addition to the data rate and feedback requirement. The results of this novel approach clearly show the dependence of the system parameter selection on the local topographical environment, and the importance of codebook size and generation as well as channel estimation.

Knowledge of the Ricean K factor is important in many communication applications as it reveals the fading severity experienced by a wireless receiver. In this paper, a statistical analysis of the maximum likelihood estimator (MLE) of K from complex (I/Q) Ricean channel samples is derived. Based on our analysis, an improved estimator of the K factor is proposed with superior bias and efficiency properties for short data records. The lack of robustness of the tractable MLE in mobile applications is addressed by incorporating a reliable estimator of the specular Doppler shift. The simulation results show that the proposed technique can outperform prior methods for I/Q mobile channel snapshots.

A reduced-complexity time-domain equalization scheme for wideband turbo-multiple-input multiple-output (turbo-MIMO) systems is presented. This scheme, called iterative trellis search equalization, is based on a modified version of the M-Bahl-Cocke-Jelinek-Raviv (M-BCJR) algorithm, applied to a suitably chosen trellis representation of the wideband MIMO channel process. Exploiting the properties of quadrature amplitude modulation (QAM) signal constellations with block-partitionable labels, this modified M-BCJR algorithm has complexity per bit that is independent of the constellation size, and polynomial in the number of transmit antennas and channel memory. Results from computer simulations show that the new scheme successfully mitigates intersymbol interference even if only a very small fraction of trellis state transitions is considered. It is also demonstrated that asynchronous transmission of the spatially multiplexed symbol streams can result in considerable performance improvement compared to synchronous MIMO systems.

Exploiting the full spatial diversity available in mobile wireless channels is most effective when some information about the channel is available at the transmitter. In many practical applications, such information is rapidly outdated and has limited realizable benefits. This note investigates the feasibility of linear fading prediction, applied to noisy channel estimates. The predictions are then used for antenna subset selection for space-time block coding. It is shown, using synthesized and measured channel data, that multidimensional prediction from short channel snapshots is unreliable for dense scattering channels. However, the use of parallel predictors can provide a significant increase in the diversity, and hence performance, achievable with antenna subset selection relative to outdated or no channel information at the transmitter.

This paper presents a reduced-complexity soft-input soft-output detection scheme, called iterative tree search detection, for multiple-input multiple-output wireless communication systems employing turbo processing at the receiver. In this scheme, a reduced search space is selected with the aid of the M-algorithm, and QAM signal constellations with block partitionable labels are used in order to make the detection complexity per bit almost independent of the modulation order, as well as asymptotically linear in the number of transmit antennas. Results from computer simulations are presented which demonstrate the capability of the scheme to approach optimal performance at considerably reduced complexity.

This work presents a reduced-complexity soft-input soft-output detection scheme for wideband space-time bit-interleaved coded modulation (ST-BICM) MIMO systems. This scheme, which is referred to as iterative trellis search detection, is based in part on a reduced-complexity variant of the BCJR algorithm. It also uses signal sets with block partitioning labeling, called multilevel mapping constellations, in order to achieve further complexity reduction for higher-order QAM modulation formats. Results from computer simulations of an iterative ("turbo") MlMO receiver employing the new scheme have shown that it successfully eliminates the error floor that occurs if inter-symbol interference is not mitigated. It is also shown that the optimum choice of the number of fingers employed by the detector is not only dependent on the channel characteristics, but also by the fraction of states considered in the trellis search.

Analytic expressions are derived for the degradation in the mean-square error performance of subspace-based array processors resulting from estimation errors. These expressions are applied in the case where the errors are the result of estimation using a finite number of data samples.

Frame synchronization is traditionally achieved by inserting a given sequence periodically into the data stream. Here, a new method of synchronization is introduced in which the synchronization sequence is not contiguous, but is interleaved with the data symbols. The properties of these distributed sequences are investigated, and requirements are specified for detectability of these sequences when inserted in random data. Methods for constructing and searching for good sequences are presented. It is demonstrated that this new method reduces the probability of false synchronization over traditional methods in the presence of additive white Gaussian noise.

For channels which suffer predominantly from additive noise and intersymbol interference, the decision-feedback equalizer has provided a relatively simple solution for reducing the effects of interfering symbols at the input to the decision device. A technique is developed that enables fast, accurate calculation of the error performance of decision-feedback equalization for a number of channel models. The method is to calculate the n-step transition probability for an associated Markov process and then use this transition probability as an approximation to the stationary probability distribution. For systems with finite memory, it is proved that the method converges. If the signal-to-noise ratio (SNR) is high and the signal amplitude is more than twice the worst-case interference, it is shown that the convergence is rapid. Numerical results indicate that the convergence is rapid enough to make this an efficient method of calculation, even for channels for which the interference does not fully satisfy this condition. Two examples are given here, but the technique has been tested on most of the examples that have been presented in the literature. The method yields results in closer agreement with simulation results than previous results obtained using bounding techniques, especially at low to moderate SNRs, and requires less computation.

Optimization of the performance of multicarrier transmission over a linear dispersive channel is presented. The optimum data and power assignment to the subcarriers are derived for both the conventional error probability criterion, and a new criterion based on the normalized mean-square error. The assignments and algorithms hold for channels where performance is degraded by additive noise, intersymbol and interchannel interference. Lower bounds on throughput are derived and are used to compare multicarrier performance with conventional single-carrier quadrature amplitude modulation (QAM) with both linear and decision feedback equalization. It is seen that multicarrier transmission can provide a significant improvement at low and intermediate channel signal-to-noise ratios. As an example, the optimization is applied to the high-speed digital subscriber loop, and multicarrier transmission is demonstrated to be superior to decision feedback equalized single-carrier QAM.