In this paper, we consider the problem of joint adaptive beamforming from multiple Access Points (APs), equipped with array antennas, to multiple single-antenna User Equipments (UEs). We derive an iterative algorithm for Multi-Cell Beam-Forming (MCBF) under per-cell power constraints and the constraint that a UE may receive data transmission from a single AP. The scheme is suitable for coordinated beamforming downlink transmission in a Coordinated Multi-Point (CoMP) cellular network. Simulation results indicate that as compared to uncoordinated transmission by means of a Grid of Beams (GoB) based Space Division Multiple Access (SDMA) scheme, MCBF offers much higher throughput for cell-edge UEs. For a single cluster of nine sectorized cells with four-element antenna arrays in an urban macro-cellular environment, MCBF obtains a 13 fold increase in 5 percentile user throughput at 2 bits/s/Hz/sector cell throughput as compared to GoB-SDMA.

In this paper, we explore a method for interference suppression in EGPRS (also commonly known as EDGE) systems, wherein 8PSK is used as the modulation for the desired signal and the interferer is modulated using GMSK. Previous methods for single antenna interference cancellation (SAIC) have concentrated on the case when both the desired and interfering signals are GMSK modulated, or have relied on highly complex methods such as joint demodulation. We derive a simple method that exploits the redundancy inherent in the interferer signal to suppress it. The interference suppression method causes a well- modeled nonlinear distortion to the 8PSK signal. This non-linear distortion is handled using a modified equalizer that deals with a time-varying input symbol constellation applied to a matrix channel. Simulation results using the method show great promise.

In this paper, we describe a transmit diversity technique for canceling partially-known interference. For a single interferer in a flat fading channel, the desired user transmitter transmits conjugated and time-reversed interferer symbols in two successive symbol periods (or subcarriers) along with one desired user symbol. The interferer symbols are scaled to have the same received power as that received from the interfering transmitter. This causes the received interference channel matrix (over the two symbol periods) to be singular, allowing interference cancellation by means of a linear filter. Transmit diversity based interference cancellation (TDIC) can, thus, be viewed as the opposite of the Alamouti code which maximizes the determinant of the received signal channel matrix. We derive interference canceling and minimum mean square error (MMSE) receivers for TDIC transmission and obtain their capacity expressions. Numerical results indicate large gains over spatial reuse transmission at low signal-to-interference ratios.

In an Orthogonal Frequency Division Multiplexing (OFDM) system, the channel is often modeled as a two-dimensional zero-mean Gaussian random process in time and frequency with known second order statistics. With pilot symbols placed across the time-frequency plane, the channel's response at a particular time-frequency point can be derived from its correlation with the nearby pilot locations. However, this a priori channel statistics may not always be available or the channel may not even be stationary to be adequately characterized by a correlation function. In this paper, we introduce a model of time-varying channel based on its delay-Doppler response. We show that a widely adopted time-frequency correlation model, upon which popular channel estimators for OFDM are often based, can be viewed as a special case of such a model with separable statistical profiles imposed on the delay-Doppler plane. Without using any statistical assumption on the channel, we derive a classical estimator based on the two-dimensional delay- Doppler correlator, which can be implemented using Discrete Fourier Transforms (DFT) of the pilot symbol measurements. Simulation results show promising performance even when the pilot symbols' insertion rate is at the channel's maximum delay-Doppler spread.

An optimum closed-loop multiple-input-multiple-output (MIMO) scheme requires a large amount of instantaneous channel information to be fed back from the receiver to the transmitter. Another closed-loop MIMO scheme called (selective) per antenna rate control (S-PARC) requires much less feedback. However, it does not perform well in conditions of low SNR, correlated antennas and Ricean fading where the number of independently coded and modulated data streams that can be supported by the channel, K, is less than the number of transmit antennas M. This is because S-PARC uses K out of M antennas to transmit the streams, which limits its capacity. The problem can be alleviated by using all antennas to transmit the streams. This is done in multiple stream co-phasing (MSC) by partitioning the set of M transmit antennas into K mutually exclusive subsets for transmission of K independent data streams after "co-phasing". Co-phasing can be considered as instantaneous beamforming where relative phase rotations (co-phasing angles) are applied to antennas for transmission of a stream. The co-phasing angles for each stream are designed to maximize the stream capacity (approximately). A minimum mean square error - successive interference cancellation (MMSE-SIC) receiver is used in MSC, as in S-PARC. MSC requires feedback of K rates and M-K angles, i.e. M real coefficients, same as in S-PARC. The average capacity of the various schemes is evaluated for 4times4 and 4times2 MIMO systems for flat Rayleigh and Ricean fading with antenna correlation. It is found that in the presence of fewer receive antennas than transmit antennas, low SNR, antenna correlation and Ricean fading, MSC greatly outperforms S-PARC. This is because MSC uses all antennas to transmit an adaptive number of streams after co-phasing, achieving high SNR. MSC closely approaches the capacity of optimum closed-loop MIMO for the entire SNR range for all channel models considered. Thus, the restriction of antenna set partitioning greatly reduces the amount of feedback in MSC, as compared to optimum, without significantly compromising performance.

In this paper, we present an effective method for suppressing spatially and temporally correlated interference. The method treats adjacent temporal samples of the received signal as signal branches coming from additional antennas and uses conventional methods for cancelling spatially correlated interference to decorrelate blocks of spatio-temporal signal samples. Based on a maximum-likelihood formulation, two algorithms for jointly estimating the channel response, the synchronization position, and the spatio-temporal block decorrelation matrix are derived. A multiple-input-single-output prefilter is used to combine the multiple signal branches generated by the proposed method into a single branch so that conventional single-branch equalizers can be employed. In the case of single-antenna interference cancellation (SAIC) in GSM terminals, the proposed technique achieves substantial performance gains over conventional interference-rejection techniques in various interference scenarios.

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.

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.

A trellis-based multiuser detection algorithm called bias compensated matched filter decision feedback sequence estimation (BCMFDFSE) is considered for DS-CDMA systems under frequency-selective fading environments. The development of the wideband DS-CDMA standard demands the consideration of frequency selectivity in designing systems. In this paper, we propose BCMFDFSE as a possible receiver structure that has nice performance/complexity tradeoffs. We compare BCMFDFSE with other algorithms such as successive interference cancellation (SIC) and parallel interference cancellation (PIC).

Decision feedback sequence estimation (DFSE), which is a reduced-complexity alternative to maximum likelihood sequence estimation (MLSE), can be used effectively for equalization of intersymbol interference (ISI) as well as for multiuser detection. The algorithm performs very well for whitened (minimum-phase) channels. For nonminimum-phase channels, however, the algorithm is not very effective. Moreover, DFSE requires a noise-whitening filter, which may not be feasible to compute for time-varying channels such as a multiuser direct-sequence code division multiple access (DS-CDMA) channel. Noise-whitening is also cumbersome for applications that involve bidirectional equalization such as the global system for mobile communication (GSM) system. In such conditions, it is desirable to use the Ungerboeck (1974) formulation for sequence estimation, which operates directly on the discrete-time unwhitened statistic obtained from conventional matched filtering. Unfortunately, DFSE based on matched filter statistics is severely limited by untreated interference components. We identify the anticausal interference components, using an error probability analysis. This leads us to a modified unwhitened decision feedback sequence estimator (MUDFSE) in which the components are canceled, using tentative decisions. We obtain approximate error probability bounds for the proposed algorithm. Performance results indicate that the modified algorithm, used on unwhitened channels with relatively small channel correlations, provides similar performance/complexity tradeoffs as the DFSE used on the corresponding whitened minimum-phase channels. The algorithm is especially attractive for multiuser detection for asynchronous DS-CDMA channels with long spreading codes, where it can achieve near-MLSE performance with exponentially lower complexity.