This paper compares the performance and complexity of various MIMO receiver structures for 802.11n WLAN systems, including linear approaches such as MMSE and ZF, and iterative detection and decoding using list sphere decoding. Optimal beam steering with the low-complexity MMSE receiver is shown to outperform the computationally-expensive list sphere decoder receiver with an uninformed transmitter

A method for predicting packet error rates in MIMO-OFDM WLAN systems is presented. The method is based on using post-detection SNRs as an abstraction of the physical layer, and is motivated by the need for a simple and efficient way of modelling the physical layer in system level simulation scenarios involving multiple stations. The physical layer abstraction is sufficient for generating error processes in the system simulations that accurately reflect the interaction between the MIMO-OFDM physical layer and the underlying wireless channel. We validate the abstract model by comparing packet error rates predicted by the model with packet error rates obtained through full link simulations for two different approaches to MIMO processing, referred to as spatial spreading and eigenvector steering.

This paper presents two transmission techniques for MIMO OFDM communication, referred to as spatial spreading and eigenvector steering. Spatial spreading is used when the transmitting station is not presumed to have sufficient channel state information to compute optimum steering vectors. This situation may occur for a variety of reasons, including poor or aged channel estimates or lack of calibration between the transmit and receive antenna chains. Eigenvector steering is used in cases where the transmitting station has sufficient information about the channel to compute optimum transmit steering vectors. Simulation results showing throughput and range achieved by the two transmission strategies are provided.

Statistics and system performance results derived from the outdoor measurements performed with a true multiple-input-multiple-output (MIMO) wideband channel measurement system are presented. These results are applicable to the MIMO channel modeling particularly for a model with paths at different time delays (tapped-delay line model) and an associated correlation matrix for each time delay.

The performance of a multi-rate IS-95 based CDMA packet data system is examined. Both the uplink and downlink channels are analyzed in a multi-user, multi-rate environment for a single 1.25 MHz carrier. On the uplink, the throughput-delay performance is evaluated for a connectionless access protocol. On the downlink, the throughput-delay performance is derived by applying standard queuing models to simulation results describing the system throughput. Load control policies are presented for both links along with simulated performance data. The results demonstrate that the multi-rate CDMA packet data system can deliver more than twice the net throughput of voice services with the same spectral efficiency.

Issues encountered in the design of reliable narrowband time-division multiple access (TDMA) digital cellular mobile communication systems are considered. In particular, the problem of compensating for the harsh multipath fading environment in systems whose transmission bandwidth is commensurate with the coherence bandwidth of the fading channel is considered. A TDMA channel characterization parameter, the slot-normalized fade rate, is introduced, and an adaptive bidirectional equalization technique, which estimates the location of a deep fade within a time slot, is proposed. The simulation results show that the carrier-to-noise ratio requirement is only 15.5 dB when this equalization technique is used. This is achieved without diversity, and with low complexity. An equivalent equalized land mobile radio channel model and the analytical solution for the optimal bit likelihood calculation for pi /4-shift quadrature differential phase-shift keying (QDPSK) modulation are also derived under certain channel conditions. The results are used as soft decisions for the convolutional decoder.>

An L-frequency trellis coding scheme designed for fading channels that provides diversity up to order L is described. L-frequency coding is advantageous over channel coding schemes that achieve implicit time-diversity through trellis coding in conjunction with time-interleaving because it requires negligible end-to-end delay. The authors derive an upper-bound for the probability of symbol error of the L-frequency code. Based on this upper-bound, they then deduce the design criteria for optimum L-frequency codes. A numerical approximation to this upper-bound and the design of a two-state and two four-state, two-frequency codes are presented. Through simulations, it was found that relative to the traditional dual frequency diversity approach, the two-state and four-state codes achieve 3- and 4-dB coding gains, respectively. This energy efficiency gain can be translated into a spectral efficiency gain. A brief discussion on the difference in code design techniques for the Gaussian channel and the fading channel is also presented.>

The use of autoregressive parameter estimates is a well known technique for estimating the frequency of a sinusoid in white noise, whose phase and amplitude are perhaps also unknown. A more challenging problem is the problem associated with first detecting signal presence and then estimating one or more unknown parameters. This paper addresses the primary problem of detecting a signal, such as a sinusoid, with one or more unknown parameters, such as relative phase, frequency or bandwidth. The use of the autoregressive parameter estimation methods for detecting such signals is discussed, as well as the use of more conventional methods based on the Periodogram or other Fourier techniques. Performance comparisons are made based both on analysis and digital computer simulation.

Results of an investigation of algorithms for estimating and suppressing narrow-band interference in pseudonoise (PN) spread-spectrum digital communication systems are presented. Techniques for determining the coefficients of a linear, interference suppression filter are described, which are based on linear prediction and conventional spectral analysis methods. Numerical results are presented on the characteristics of the linear filter and on its effectiveness in suppressing the interference. The error rate performance of a receiver that employs the interference suppression filter followed by a PN correlator is determined based on the assumption that the combined noise and residual interference at the output of the PN correlator is Gaussian distributed. Performance results obtained by Monte Carlo simulation are also presented and compared with theoretical results.