MIMO and higher-order modulation (64-QAM) have recently been introduced in the HSPA downlink (HSDPA) to extend peak data rates. Both techniques demand a high SINR operating point in order to be effective. While traditional macrocell (outdoor) deployments may provide limited high-rate coverage, indoor environments are more likely scenarios for achieving high rates due to higher SINR operating points. This paper evaluates performance for an indoor pico-cell system using a selective-PARC (S-PARC) MIMO scheme in combination with 64-QAM. A typical multi-story office building is considered with pico-cells located on each floor. Within each pico-cell both a single antenna cluster and distributed antenna clusters are considered. Results from system simulations show very large gains in both user and system throughput compared to a receive diversity only system. 90th percentile user throughput over 40 Mbps and system throughput of 30 Mbps are achieved.

For multiple-input, multiple-output (MIMO) antenna systems, it is necessary to evaluate performance under realistic propagation channels that include spatial correlation and dispersion. Models developed for this purpose must have enough flexibility to handle different antenna configurations and propagation scenarios. In this paper, the recently proposed 3GPP spatial channel model is extended to three-dimensional scattering using ellipsoidal sub-regions to model time dispersion. We further develop an analytical formulation of the space-time correlation function, allowing traditional methods to generate correlated fading realizations. We show that the 3D model reduces correlation compared to 2D propagation, and evaluate correlation properties for different antenna orientations, showing that averaging over random receive antenna orientations both reduces correlation and its dependence on the base to mobile distance.

In mobile communication systems, downlink (forward link) system capacity is limited by the ability of mobile receivers to recover the desired signal in the presence of cochannel interference (CCI). Joint detection of the desired and cochannel signals is a useful approach to improving receiver performance, thus increasing system capacity. In this paper, we show that a practical single-antenna joint-detection receiver can provide significant gains in system capacity for the time-division multiple-access (TDMA) standard Telecommunications Industry Association/Electronic Industry Association/Interim Standard-136 (TIA/EIA/IS-136 or IS-136). For a sectorized system, joint detection provides a capacity gain of 47% in a typical urban environment. When used in conjunction with transmit beamforming, the synergy between the two approaches leads to a capacity gain of over 200%. In determining these gains, practical aspects of the IS-136 system are considered, namely, unsynchronized networks, limited receiver complexity, and adaptability. A semiblind acquisition process, which uses the training sequence of the desired user only, is employed, because the desired and interfering base stations are not synchronized. The receiver complexity is controlled by processing only one sample per symbol period, even though it is shown that multiple samples per symbol period should ideally be used. Finally, because receiver performance may be limited by its own intersymbol interference instead of CCI, an adaptive joint-detection process is used which selects between joint demodulation and single-user equalization for each slot.

MISO antenna systems employing feedback of the downlink channel state are attractive for achieving diversity in the downlink of cellular systems. In this paper we consider a particular MISO transmit diversity scheme with rich feedback (TDRF), and derive the optimal receiver structure taking into account intersymbol interference, colored noise, and the self-interference from pilot signals used for downlink channel estimation. We then compare the bound on performance established by the optimal receiver with the performance of a low complexity alternative consisting of a fixed receive filter followed by a sampler. Our results show that the application of TDRF to the WCDMA downlink gives substantial gains compared to a single antenna system, even when the extremely simple sampler receiver is used at the mobile terminal.

In this paper, we propose an adaptive joint detection receiver for co-channel interference cancellation in ANSI-136 handsets. The proposed receiver adaptively mitigates the dominant impairment present in the system: performing two-user joint demodulation in the presence of a dominant interferer and resorting to single-user equalization in a noise or inter-symbol-interference-limited system. The choice for the demodulator is based on the residual impairment power estimates obtained from single-user and joint acquisition using the training symbols of the desired user. Simulation results for a 1900 MHz ANSI-136 system indicate that the adaptive receiver performs well in various environments. By selecting the best demodulator for each slot on the basis of instantaneous channel conditions, the adaptive detector outperforms both single-user and joint detectors in fading channels.

Joint demodulation techniques have been shown to be effective in mitigating co-channel interference for mobile handsets with only a single receiver antenna. As in the case of single user demodulation, a joint demodulation receiver needs to calculate the soft information values corresponding to the desired signal to optimize decoder performance. In this paper, practical soft information generation algorithms for use with joint demodulation of co-channel signals are described. The proposed algorithms are evaluated using the transmission parameters of a time-division multiple-access (TDMA) system known as American National Standards Institute-136 (ANSI-136).

Coherent joint detection of cochannel signals is an effective method for improving quality and system capacity for narrow-band TDMA systems in the presence of interference. Accurate estimation of signal parameters is thus required in order to separate the signals for different users. This paper proposes an accurate method for estimating phase and frequency errors that are present in the received signal. Combined with multi-user sequence estimation, an approach is developed that uses a cross-coupled, digital phase-locked loop (DPLL) to track the phase and frequency estimates during demodulation. Additionally, the frequency estimates are smoothed across multiple data slots to improve the performance. Simulation results are presented showing the efficacy of this approach to compensate for phase and frequency errors present in single-antenna ANSI-136 handsets.

In this paper, successive cancellation of co-channel signals is described in the context of TDMA mobile radio systems employing coherent receivers. Both symbol aligned and misaligned co-channel signals are studied. Signal separability, which is a major problem in successive cancellation of co-channel signals, is obtained using the relative timing delay between co-channel signals. Both hard and soft subtractions are examined. Soft subtraction, where the estimated values are weighted with some reliability measure, leads to significant C/I gains for both coded and uncoded bits.

Array processing is a promising approach for improving quality, coverage, and capacity in digital cellular communication systems. By combining array processing with maximum likelihood sequence estimation (MLSE), intersymbol interference (ISI) introduced by multipath propagation can be mitigated as well. Novel symbol-spaced and fractionally spaced adaptive array processing MLSE receivers are developed for both diversity and phased array antenna configurations. The practical issues of synchronization and channel estimation are addressed. A novel approach to automatic frequency error correction (AFC) is proposed and is shown to be critical when cancelling cochannel interference. Performance is evaluated for the reverse link of the IS-136 TDMA-based digital cellular system. Substantial improvements are obtained over conventional antenna configurations for receiver sensitivity (2.5-4 dB) and over traditional antenna combining when cochannel interference is present (0.5-25 dB).

The application of a Markov random field (MRF) state model in an expectation-maximization (EM)-based approach to unsupervised image segmentation is investigated. In the calculation of the marginal distribution of the state field, it is shown that the use of the expected state values for interacting pixel sites in the computation of the MRF energy function may be interpreted as a mean-field approximation. The implications of calculating a self-consistent expectation of the state field are considered. EM convergence criteria are considered, and a criterion based upon divergence is proposed. Experimental results based on synthetic data illustrate the performance advantage of the mean-field approximation and the computational advantage of using self-consistent expectations.>