Lattice reduction (LR) aided MIMO detection has been shown to provide near-optimal hard outputs. However soft outputs are required in practical systems to fully exploit gains from forward error correction. Due to the non-linear nature of LR aided MIMO detection, generating soft information on the estimates it provides is not trivial. Consequently this problem has not been treated much in the literature. In this paper we present two related algorithms for computing soft outputs on estimates of LR-aided MIMO detection. It is shown through computer simulations that the proposed soft output generation algorithms allow LR-aided MIMO detection to achieve near- optimal performance for coded systems.

This paper analyses lattice reduction for MIMO decoding and investigates how different parameters affect the complexity. Lattice reduction is a promising technique and a common approach to implementing it is to use the LLL algorithm. In this paper we show how the complexity of the LLL algorithm depends on such parameters as the number of antennas, SNR, channel correlation and channel matrix column sorting. Both real- and complex-valued versions are considered and complexity-performance trade-offs are also studied.

In this paper we propose an analog VLSI approach to maximum a posteriori (MAP) detection in multiple-input multiple-output (MIMO) systems. This detector can be seen as an extension of the well known analog decoding concept for error correcting codes, as it is constructed using similar building blocks. Therefore, it can naturally interact with analog decoders in order to perform turbo detection in MIMO systems. First transistor-level simulations for a small analog MIMO detector in a 0.25mum BiCMOS process agree well with floating-point digital simulations

This paper presents an analysis of frequency-offset estimation in multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems. Tracking of the frequency offset between a transmitter and a receiver is often aided by transmitting pilots embedded in the data payload of a packet. The extension to multiple-antenna OFDM systems means that spatial beamforming will occur when transmitting pilots from all antennas simultaneously, which can reduce the robustness of frequency-offset estimation. This paper presents a thorough analysis of the spatial beamforming problem, and shows how the spatial correlation of the MIMO channel impacts performance. Simulation results are presented for both synthetic and measured channels, which agree well with the theoretical results

This paper presents an analysis of frequency offset estimation in MIMO OFDM systems. Tracking of frequency offsets is often aided by pilots transmitted in the data payload of a packet. The extension to multiple antenna OFDM systems means that spatial beamforming will occur when transmitting pilots from all antennas simultaneously, which can reduce the robustness of frequency offset estimation. We present a thorough analysis of the spatial beamforming problem and show how the spatial correlation of the MIMO channel impacts the performance. Simulation results are presented for measured channels recorded in an office environment, which agree well with the theoretical results.

The paper presents the analysis of spatial correlation in MIMO channels, calculated from data measured in office environments at 5.2 GHz. Results are compared with those from channels generated using a stochastic MIMO channel model and the effect of different comparison metrics is shown. The suitability of the stochastic model under different propagation conditions is also investigated. The performance of the models has been shown to be good under non-line-of-sight (NLOS) propagation, although one model was shown to fail under conditions where the correlation amongst the elements of one array was not independent of the antenna element at the other array. It is shown how situations in which array correlation varies with array element can occur in line-of-sight (LOS) conditions, and how under these extreme circumstances, both stochastic models are unsuitable.

Herein, results of 5.2 GHz wideband indoor multiple input multiple output (MIMO) channel measurements under the EU IST SATURN project are reported. Our investigation shows that for non-line-of-sight (NLOS) cases, the average power delay profiles fit the exponentially decaying curve quite well, therefore a simple wideband model for single-input single-output (SISO) proposed in COST259 has been used in our model. Furthermore, the investigations show that the MIMO channel covariance matrix of each normalized tap of the impulse response could be well approximated by the Kronecker product of the covariance matrices seen from the transmitter and receiver respectively. Based on the above results, a wideband statistical model is presented. Monte-Carlo simulations show reasonably good agreement between the measured data and our model. Finally, we use this model to show some capacity characteristics of Hiper-LAN/2 channels in NLOS indoor scenarios.

Downlink beamforming in a WLAN-type system employing access points and mobiles equipped with multiple antennas and associated receivers and transmitters are considered. The beamforming aims at maximizing the performance under constraints on transmit power or equivalent isotropic radiated power (EIRP). Solutions for the two constraints are derived and investigated using simulated and measured channels. Our simulation and experimental results shows that performance gains of 8-10 dB when using four directional transmitter antennas and two receive antennas (as compared with a base-line one-transmit two-receive), are possible under both constraints. For simulated channels, a delay between channel estimation and use of the same channel of up to 10% of the (inverse of the) Doppler frequency only degrades performance some tenths of a dB. In our measurements, very small degradations are seen with delays of up to 130 ms. The measurements were made under relatively stationary conditions with only occasionally moving people. Two different strategies for updating the beamforming vectors: sounding and ping-pong, are also considered in the paper.

Herein, results from measurements conducted by the University of Bristol are presented. The channel characteristics of multiple input multiple output (MIMO) indoor systems at 5.2 GHz are studied. Our investigation shows that the envelope of the channel for non-line-of-sight (NLOS) indoor situations are approximately Rayleigh distributed and consequently we focus on a statistical description of the first and second order moments of the narrowband MIMO channel. Furthermore, it is shown that for NLOS indoor scenarios, the MIMO channel covariance matrix can be well approximated by a Kronecker product of the covariance matrices describing the correlation at the transmitter and receiver side respectively. A statistical narrowband model for the NLOS indoor MIMO channel based on this covariance structure is presented.

The measurement and characterisation of multiple-input multiple-output (MIMO) channels has gained increasing attention over recent years. Previous analysis of MIMO measurements has generally focussed on the evaluation of the capacity of such systems in differing locations and configurations. We present measurements made in an indoor environment at 5.2 GHz, specifically to investigate temporal channel variation. Line-of-sight and non-line-of-sight situations are compared by means of an analysis of the rate of variation in the powers of the 'orthogonal spatial channels' comprising the overall MIMO channel. The conclusions are extended to encompass the rate of variation in performance of MIMO channels under different environmental conditions.

A WLAN-type scenario where a base-station (access point) equipped with multiple antennas is transmitting and a mobile with only a single antenna is receiving, is considered. Three approaches are investigated: grid-of-beams (GOB), maximal-ratio (MR) and equal-gain (EG), each with one of the following constraints 1) total transmit power over all antenna elements, 2) maximum power on any antenna element 3) equivalent isotropic radiated power (EIRP). The median diversity gain for the MR approach is estimated to be 14.8 dB, 10.6 dB, and 11.4 dB using constraint 1-3, respectively at 5.2 GHz in a modern university building at 5-50 meter range. For GOB corresponding numbers are 9.4 dB, 9.4 dB, 2.3 dB and for EG 13.9 dB, 13.9 dB, 10.3 dB, respectively. These results are virtually independent of delay between channel estimation and use of the same estimate, when the delay is less than 130 ms. This result is obtained although there were people moving in the environment. The diversity gain under the EIRP constraint is encouraging and shows that coverage improvements are possible even under EIRP limitations.