This work considers the placement of pilot symbols in orthogonal frequency division multiplexed transmissions, to minimise the mean squared error in the corresponding channel estimation. We show that further improvements in this widely investigated topic are possible, for example, in indoor wideband channels, which are subject to significantly correlated scattering processes. Noting that the naive approach incurs a prohibitive complexity, low complexity greedy solutions are developed. A measurement campaign is conducted to estimate real-world channel statistics in an indoor wideband environment. It is confirmed that practical channels are correlated, even to the extent of exhibiting rank deficiencies, and that the proposed placement algorithms result in improved channel estimation performance.

If antenna selection in OFDM is done on a per-tone basis, the frequency domain can be exploited to achieve very good performance. However this means that the channel after antenna selection will have discontinuities in the frequency domain. In this paper we present a novel phase precoding that ensures that the channel after antenna selection is smooth enough in the frequency domain for advanced channel estimation. We analyse its performance and show that it is robust to channel estimation and reciprocity errors.

To facilitate coherent detection of orthogonal frequency division multiplexed transmissions, pilot symbols can be transmitted in some of the subcarriers. Their placement to minimise the mean squared error in channel estimation is considered. Such problems have been widely addressed previously for channels subject to wide sense stationary uncorrelated scattering processes. While the stationarity assumption is usually realistic, indoor wideband channels, for example, are subject to significantly correlated scattering processes. Furthermore, practical multiple antenna transmitters/receivers are bound to exhibit spatial correlations. This work considers pilot placement optimisation in a multiple antenna setting subject to arbitrary correlations in the delay and spatial domains. Noting that the naive approach incurs a prohibitive complexity, low complexity greedy solutions are developed. It is further proven that the conventional equi-spaced placement becomes optimal at high SNR even with correlations, when the correlation matrices are of full rank. A measurement campaign is conducted to estimate real-world channel statistics in an indoor wideband environment, and observe the applicability of developed algorithms. It is confirmed that practical channels are correlated to the extent of exhibiting rank deficiencies, and that the proposed placement algorithms result in improved channel estimation performance.

The linear minimum mean-squared error (MSE) channel estimator for systems employing per-subcarrier transmit antenna selection is developed. Frequency domain correlations after the selection process are shown to be approximated well using a simple function, which makes near-optimal channel estimation practically possible. However, the resultant estimators are not robust to errors in the assumed model, in terms of the antenna-to-subcarrier assignment used at transmission, as we motivate both analytically and via simulations. This is an issue when the channels for conveying this information to the receiver are severely constrained. We present windowed channel estimations and new robust estimation algorithms, either individually or in combination, as solutions to counter this sensitivity. The robust estimators are developed based on the principles of 1) minimising the worst case MSE over the set of possible models and 2) minimising the expected MSE over the set of possible models. The latter estimator is preferred due to the lower implementation complexity and better MSE performance. We also prove theoretical asymptotic (in signal-to-noise ratio) performances of the two estimators used with the proposed correlation model. Simulation results illustrate the performance gains and improved robustness offered by the developed estimators.

The linear minimum mean-squared error (MSE) channel estimator for systems employing per-subcarrier transmit antenna selection is developed. It is shown that the frequency domain correlations after the selection process is approximated well using a simple explicit function. Performance of resultant estimators, which assume a certain correlation model, deteriorates quickly at high signal-to-noise ratios (SNR) when model errors exist. To overcome this deficiency, robust estimators based on the principles of minimising the worst case and expected MSEs over the possible model set are developed. Solution to the latter is given in closed form, and is seen to achieve MSE optimal performance at low SNR while the high SNR performance is the same as that of the least-squares (LS) estimator. The optimal estimator with the proposed correlation function and correct model knowledge performs about 3 dB better than the LS estimator at a packet-error-rate of 0.01 for a channel coded system employing 16-QAM modulations, whereas in the presence of model errors, the latter robust estimator is performing about 2 dB better than the LS estimator.

A static and dynamic reconfiguration method and apparatus that can be utilized for parallel turbo decoding is described. The methodology is based on the property of a class of polynomials that can provide contention free permutation. A new ring interconnect methodology is presented that can be used for quadratic permutation polynomial (QPP) based interleaved memory access. An efficient interleave-deinterleave mechanism using QPP interleaver is also presented for a new power driven reconfigurable solution. It consists of multiple SISO modules connected by a mix of dynamic and static reconfigurable interconnect with an efficient memory segmentation that matches the underlying reconfigurable fabric. The parallel blocks are controlled by a unified state machine mapped external to the reconfigurable fabric. The overall array is implemented on 90nm Toshiba standard cell library occupying an area of 11.11 mm2 with reconfigurable speeds of 7.8-131.28 Mb/sec and the corresponding power consumption of 53-762 mW.

Detection of OFDM transmissions with interspersed pilot symbols is considered. A hard output detection algorithm developed by Taricco et. al. for flat fading channels is extended for this frequency selective scenario. In the investigated systems with 128 subcarriers, this algorithm outperforms conventional approaches and performs close to a genie aided receiver even with the use of a single pilot symbol for the whole frame. Furthermore, a novel soft output generating algorithm is developed, which is more suitable for channel coded systems. The resultant algorithm is capable of detecting coded OFDM transmissions with fewer pilot symbols than that required for noiseless channel identification.

A novel methodology of transmit beamforming for systems subjected to equivalent isotropic radiated power restrictions is presented in this paper. Based on the properties of the radiation due to the optimal beamforming method compared with that due to the eigen-beamforming, beamforming vectors are designed by perturbing the scaled eigen-beamforming vector such that the peak-to-average power ratio of the spatial radiation is reduced. Two algorithms incorporating this general methodology are presented. With a computational complexity less than the optimal method, both are shown to outperform conventional sub-optimal beamforming methods. For example, in an investigated system with four transmit and one receive antennas, performance is improved by more than 1 dB at a packet-error-rate of 10−3.

Certain communications transmitters are restricted by their equivalent isotropic radiated power (EIRP) rather than the total transmitted power. Important examples are ultra-wideband systems. Use of channel knowledge at transmission for such systems, when there are multiple transmit antennas, is complicated due to the need to consider the spatial directivities of the radiation. Thus it is computationally prohibitive to implement optimal EIRP constrained beamforming schemes. This work presents a novel low complexity transmit beamforming method for such systems. Motivated by the radiation due to optimal schemes, the algorithm is based on perturbing the dominant channel eigenvector such that the peak-to-average power ratio of the spatial radiation is reduced. Simulation results confirm the improved system performance compared to existing sub-optimal beamforming methods.

Ultra wide-band (UWB) devices conforming to the WiMediareg specification are set to become ubiquitous, with the adoption of WiMedia for wireless USB and Bluetooth 3.0. However, the performance of these devices at high data rates may be poor, as they operate at low signal powers and experience frequency selective fading. This paper therefore proposes a new transceiver design for improving the robustness and mean throughput when communicating with these devices. Performance is improved using multiple antennas, in conjunction with per subcarrier antenna selection based on channel state information at the transmitter. Legacy compliance is accomplished by using phase precoding to make transmissions appear to have originated from a single antenna system, albeit one with an associated channel that exhibits significantly reduced fading. Performance is benchmarked against legacy operation; and the impact of channel estimation and hardware calibration errors is investigated. Results show that, even with pessimistic assumptions about calibration errors, performance is improved dramatically.

Ultra wideband transceivers promise multi-gigabit per second performance at power consumptions commensurate with portable devices. Future products are likely to adopt multiple antennas to maximize performance. Severe FCC EIRP restrictions impose an interesting system design constraint. In this paper, capacity optimal multiple antenna transmission schemes are investigated for EIRP restricted systems under the assumption that the channel is known at the transmitter. It is shown that per subcarrier antenna power allocation, which reduces to antenna selection at low SNR or when using one receive antenna, is optimal for some transmitter configurations. The improvements in capacity are quantified for representative channels.

Detection of spatially multiplexed data transmissions subject to frequency flat fading is considered. Optimal decoders require knowledge of the marginal posterior distributions of the transmitted symbols, but their exact computation is not feasible for practical systems. Hence sub-optimal approaches are generally sought. By recasting this problem into the graphical model framework, we investigate here a recently proposed suboptimal approach which relies on a tree-based reparameterization principle. For quasi-static fading channels, the resulting decoder complexity has an order which is at most quadratic in the number of transmit antennas. However, in its standard form, the algorithm often fails to converge, severely restricting its practical usability. We here develop a novel methodology to ensure systematic convergence of the algorithm in this communication scenario at the expense of the introduction of a minimal bias on the computation of the symbol marginal posterior probabilities. This bias is quantified theoretically and its innocuity for the problem at hand is ultimately demonstrated through numerical simulations. For a system using 16-QAM modulation with four transmit and receive antennas, the proposed detector achieves a bit-error rate of 10-4requiring only 3 dB greater SNR than the optimal method.

BCJR algorithm is an exact and efficient algorithm to compute the marginal posterior distributions of state variables and pairs of consecutive state variables of a trellis structure. Due to its overwhelming complexity, reduced complexity variations, such as the M-BCJR algorithm, have been developed. In this paper, we propose improvements upon the conventional M-BCJR algorithm based on modified active state selection criteria. We propose selecting the active states based on estimates of the fixed-lag smoothed distributions of the state variables. We also present Gaussian approximation techniques for the low-complexity estimation of these fixed-lag smoothed distributions. The improved performance over the M-BCJR algorithm is shown via computer simulations.

This work investigates the performance of a new reduced-complexity trellis decoding algorithm (termed the EP-MBCJR algorithm) when employed for the task of equalization in an indoor multiple input multiple output wireless environment. The algorithm is a generic approximate reduced-state variation of the BCJR algorithm modeled after the conventional M-BCJR algorithm. Instead of choosing the active states based on the filtered distribution of states in the forward recursion, the EP-MBCJR algorithm selects the active states based on "beliefs" on the states. This can be seen as an application of the concept of "expectation propagation" and leads to identical forward and backward recursions which can be iterated to improve system performance. A receiver architecture comprising of channel estimation, sampling phase selection and turbo equalization is proposed and its performance evaluated through computer simulations. For the simulation of channels closely resembling the physical environment, we have used channels generated in accordance with the IEEE 802.11n TGn channel models

The inferential task of computing the marginal posterior probability mass functions of state variables and pairs of consecutive state variables of a hidden Markov model is considered. This can be exactly and efficiently performed using a message passing scheme such as the Bahl-Cocke-Jelinek-Raviv (BCJR) algorithm. We present a novel iterative reduced complexity variation of the BCJR algorithm that uses reduced support approximations for the forward and backward messages, as in the M-BCJR algorithm. Forward/backward message computation is based on the concept of expectation propagation, which results in an algorithm similar to the M-BCJR algorithm with the active state selection criterion being changed from the filtered distribution of state variables to beliefs of state variables. By allowing possibly different supports for the forward and backward messages, we derive identical forward and backward recursions that can be iterated. Simulation results of application for trellis-based equalization of a wireless communication system confirm the improved performance over the M-BCJR algorithm.