Cheran M. Vithanage

On capacity-optimal precoding for multiple antenna systems subject to EIRP restrictions

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.

Precoding in OFDM-based multi-antenna ultra-wideband systems

Next-generation ultra-wideband systems will be required to operate in a robust manner over short distances while achieving data rates on the order of gigabits per second. Sophisticated multiantenna techniques can be employed to meet these objectives; in particular, multi-antenna precoding (or beamforming) methods are promising solutions. However, due to the strict power regulations placed on UWB transmissions, conventional precoding techniques are not always suitable for use in UWB networks. In this article we present new theoretical results and practical approaches to performing precoding in OFDM-based multi-antenna UWB systems.

Robust Linear Channel Estimation Methods for Per-Subcarrier Transmit Antenna Selection

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.

Novel Reduced-State BCJR Algorithms

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.

Antenna Selection with Phase Precoding for High Performance UWB Communication with Legacy WiMedia Multi-Band OFDM Devices

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.

Reduced complexity equalization of MIMO systems with a fixed-lag smoothed M-BCJR algorithm

M-BCJR algorithm is a reduced state version of the BCJR algorithm and selects a set of active states in the forward recursion based on an estimation of the filtered probability distribution of states at each time. We propose to use instead an estimation of the fixed-lag smoothed probability distribution of states with a non zero lag. Our implementation uses a Gaussian approximation to estimate these distributions with a low complexity, using the principle of probabilistic data association (PDA). The performance of the M-BCJR can be seen to be greatly improved as a result while remaining robust against changes in the channel multipath profile.

MIMO-OFDM Pilot Placement Algorithms for Wideband Indoor Communications

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.

Dynamic reconfiguration approach for high speed turbo decoding using circular rings

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.

Approximate inference in hidden Markov models using iterative active state selection

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.

Per-Tone Transmit Antenna Selection with Phase Precoding for OFDM

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.