Trellis-coded CPFSK and soft-decision feedback equalization for micro-cellular wireless applications

In this paper, trellis-codedM-ary CPFSK with noncoherent envelope detection and adaptive channel equalization are investigated to improve the bit error rate (BER) performance of microcellular digital wireless communications systems. For the same spectral efficiency, the trellis-coded modulation (TCM) schemes studied outperform minimum shift keying (MSK) with noncoherent or differentially coherent detection in Rayleigh fading channels. For the case of frequency-selective fading channels, adaptive channel equalization is applied to mitigate the time-variant intersymbol interference (ISI). A new equalizer structure is proposed which, in its feedback path, makes use of fractionally spaced signal samples instead of symbol-spaced hard decisions on transmitted symbols. Computer simulation results indicate that the soft-decision feedback equalizer (SDFE) can significantly improve the system's performance.     

Efficient decision feedback equalization for sparse wireless channels

A new efficient decision feedback equalizer (DFE) appropriate for channels with long and sparse impulse response (IR) is proposed. Such channels are encountered in many high-speed wireless communications applications. It is shown that, in cases of sparse channels, the feedforward and feedback (FB) filters of the DFE have a particular structure, which can be exploited to derive efficient implementations of the DFE, provided that the time delays of the channel IR multipath components are known. This latter task is accomplished by a novel technique, which estimates the time delays based on the form of the channel input-output cross-correlation sequence in the frequency domain. A distinct feature of the resulting DFE is that the involved FB filter consists of a reduced number of active taps. As a result, it exhibits considerable computational savings, faster convergence, and improved tracking capabilities as compared with the conventional DFE. Note that faster convergence implies that a shorter training sequence is required. Moreover, the new algorithm has a simple form and its steady-state performance is almost identical to that of the conventional DFE.     

Turbo space-time equalization of TCM for broadband wireless channels

This paper presents a space-time turbo (iterative) equalization method for trellis-coded modulation (TCM) signals over broadband wireless channels. For fixed wireless systems operating at high data rates, the multipath delay spread becomes large, making it impossible to apply trellis-based equalization methods. The equalizer proposed here consists of a broadband beamformer which processes antenna array measurements to shorten the observed channel impulse response, followed by a conventional scalar turbo equalizer. Since the applicability of trellis-based equalizers is limited to additive white noise channels, the beamformer is required to preserve the whiteness of the noise at its output. This constraint is equivalent to requiring that the finite-impulse response (FIR) beamforming filters must have a power complementarity property. The power complementarity property imposes nonnegative definite quadratic constraints on the beamforming filters, so the beamformer design is expressed as a constrained quadratic optimization problem. The composite channel impulse response at the beamformer output is shortened significantly, making it possible to use a turbo equalizer for the joint equalization and decoding of trellis modulated signals. The proposed receiver structure is simulated for two-dimensional TCM signals such as 8-PSK and 16-QAM and the results indicate that the use of antenna arrays with only two or three elements allows a large decrease in the channel signal-to-noise ratio needed to achieve a 10/sup -4/ bit-error rate.     

Coding and equalization for PPM on wireless infrared channels

We analyze the performance of trellis-coded pulse-position modulation with block decision-feedback equalization (BDFE) and parallel decision-feedback decoding (PDFD) on indoor, wireless infrared channels. We show that the reduced complexities of BDFE and PDFD as compared to maximum-likelihood sequence detection allow for better codes whose increased coding gain more than compensates for the penalty due to suboptimal detection. We quantify these net gains in performance over a range of dispersive channels, indicating where BDFE and PDFD provide the best performance. Finally, we present Monte Carlo simulation results to verify our analysis     

Reduced complexity decision feedback equalization for multipathchannels with large delay spreads

Two modified decision feedback equalization (DFE) structures are presented for the efficient equalization of long sparse channels with strong precursor, such as those encountered in high-speed communications over multipath channels with large delay spread. Unlike the conventional DFE, these structures allow the channel's sparseness to be exploited by simple tap allocation, before the sparseness is degraded by feedforward filtering. Both structures yield large reductions in complexity while maintaining performance comparable to the conventional DPE, hence overcoming a key computational bottleneck when equalizers are implemented in hardware for speed. Fast channel estimate-based algorithms for computing the modified DFE coefficients are derived. Simulation results are presented for data rates and channel profiles of the type considered for the proposed North American high definition television (HDTV) terrestrial broadcast mode     

Cyclic delay diversity with frequency domain turbo equalization for uplink fast fading channels

Cyclic delay diversity (CDD) is an attractive diversity technique due to its low complexity and compatibility to existing wireless communication systems. This letter proposes a CDD with frequency domain turbo equalization (FDTE) for single carrier (SC) transmission, in order to achieve the full spatial diversity of frequency-selective multi-antenna channels. The frequency diversity inherent in SC is picked up from the increased channel selectivity of CDD. The noise or intersymbol interference enhanced by equalization for highly selective channels is then mitigated through applying FDTE at the receiver. Simulation results show that the performance of proposed system approaches the corresponding orthogonal spacetime block coding (STBC) system in slowly fading channels without any data rate loss, and considerably outperforms the STBC system in fast fading channels.     

时延角度扩散信道中TD-SCDMA系统下行波束技术

TD-SCDMA系统最重要技术特征是智能天线技术。本文提出了基于时延和角度扩散及天线结构的时空间信道信道模型。在此基础上研究了下行链路智能天线的波束加权方法。     

Reduced-complexity equalization techniques for ISI and MIMO wireless channels in iterative decoding

Two reduced-complexity soft-input soft-output trellis decoding techniques are presented in this paper for equalizing single-input single-output intersymbol interference (ISI) channels and multiple-input multiple-output (MIMO) frequency selective fading channels. Given a trellis representing an ISI channel, the soft-output M-algorithm (SOMA) reduces the complexity of equalization by retaining only the best M survivors at each trellis interval. The remaining survivors are discarded. The novelty of the SOMA is the use of discarded paths to obtain soft-information. Through a simple update-and-discard procedure, the SOMA extracts reliable soft-information from discarded paths which enables a large trellis to be successfully decoded with a relatively small value of M. To decode a trellis representing a MIMO frequency selective fading channel, two challenges are faced. Not only that the trellis has a large number of states, the number of branches per trellis interval is also enormous. The soft-output trellis/tree M-algorithm (SOTTMA) expands each trellis interval into a tree-like structure and performs the M-algorithm twice: once at each trellis interval to reduce the number of states and the other at each tree sub-level to remove unwanted branches. With the proposed technique, high-order trellises with million of branches per interval can be decoded with modest complexity.     

Joint MF combining and turbo equalization for wireless communications over ISI channels with diversity reception

A new method called joint Matched Filter (MF) combining and turbo equalization is proposed for wireless communications over Inter-Symbol Interference (ISI) channels with diversity reception. This method takes diversity combining and equalization as integrity and need just one turbo equalizer for all diversity branches. Computer simulations prove that our method can take advantage of turbo equalization and diversity reception to combat fading of wireless channels.     

Adaptive antenna arrays for reducing the delay spread in indoorradio channels

The performance in terms of channel delay-spread reduction resulting from the use of adaptive antenna arrays are evaluated in a typical indoor environment. The propagation channel is simulated by means of a 3-D ray-tracing program. The impact of the geometric structure of the arrays as well as of the system bit-rate is discussed     

Distance metric for soft-decision decoding in non-Gaussian channels

A new distance metric for soft-decision decoding in impulsive noise is proposed. Results reveal that soft-decoders employing Euclidean distance as a decoding metric suffer two limitations: an increase in constraint-length leads to degraded performances; secondly, their performance is poorer than hard-decoders. Both limitations are ameliorated by the proposed distance metric.     

Jointly optimized bit-rate/delay control policy for wireless packetnetworks with fading channels

We consider the downlink rate control problem in a wireless channel. A dynamic programming optimization method is introduced to obtain the optimal bit-rate/delay control policy in the downlink for packet transmission in wireless networks with fading channels. We assume that the base station is capable of transmitting data packets in the downlink with different bit rates, R₀1<···M-1 . It is assumed that the symbol rate is fixed in the system, and different bit rates are achieved by choosing the transmitted symbols from the appropriate signal constellation (adaptive modulation). The derived optimal rate control policy, in each time slot, selects the highest possible bit rate which minimizes the delay and at the same time minimizes the number of rate switchings in the network. The optimal bit-rate control problem is an important issue, especially in packet data networks, where we need to guarantee a quality of service (QoS) in the network. Our analytical as well as simulation results confirm that there is an optimal threshold policy to switch between different rates     

A model for the multipath delay profile of fixed wireless channels

This paper deals with the measurement and modeling of multipath delay on fixed wireless paths at 1.9 GHz in suburban environments. The primary focus is on the delay profile, which is the normalized plot of received power versus delay in response to an RT “impulse.” We describe measurement campaigns in the western suburbs of Chicago, IL, and in suburban north-central New Jersey. Our analysis of the data suggests to us that, for directive terminal antennas, the delay profile can be modeled as having a “spike-plus-exponential” shape, i.e., a strong return (“spike”) at the lowest delay, plus a set of returns whose mean powers decay exponentially with delay. This delay profile can be characterized by just two parameters (both variable over the terrain), namely, the ratio (K₀) of the average powers in the “spike” and “exponential” components and the decay time constant (τ₀) of the “exponential” component. No such simple structure appears to apply for delay profiles using omnidirectional antennas. For a directive antenna with a 32° beamwidth, we find that: (1) the statistical correlation between the profile parameters K₀ and τ₀ is negligible; (2) these parameters are relatively insensitive to antenna height and path length; and (3) over each measured region (Illinois and New Jersey), K₀ and τ₀ have median values close to 8 dB and just below 0.2 μs, respectively. Moreover, we have found simple probability distributions that accurately portray the variability of K₀ and τ₀ over the terrain     

Optimized decision-feedback equalization for convolutional coding with reduced delay

Error propagation is a significant problem with the decision-feedback equalizer (DFE) at low-to-moderate signal-to-noise ratios. In particular, when a DFE is concatenated with a convolutional code, the burst errors associated with error propagation can severely degrade performance, since the convolutional code is optimized for the additive white Gaussian noise channel. In this paper, we explore the compensation of error propagation in the DFE so as to break up error bursts and improve performance with convolutional codes, without incurring larger overall decoding delay. We propose certain stationary error models and derive a modified DFE (MDFE) based on these models which can compensate for the error propagation. The MDFE differs from the conventional DFE only in its tap values. The incorporation of the bias into the model and the removal of the bias during the design process is discussed. Simulations explore the performance of the MDFE for both uncoded and convolutionally coded systems. With coding, the MDFE can significantly improve on the conventional DFE in terms of bit-error rate, and the MDFE without interleaving can improve on the conventional DFE with interleaving in terms of decision delay.     

Performance of RCPC codes with soft-decision decoding overNakagami-m fading channels

The analytical upper bounds on the pairwise error probability of rate compatible punctured convolutional (RCPC) codes, using coherent BPSK signals over slow frequency nonselective Nakagami-m fading channels with AWGN, are evaluated. With perfect channel state information (CSI) assumption, we use a direct integral with the Nakagami-m probability density function to obtain a closed form upper bound. For the case without CSI, we find an approximated upper bound for the high SNR cases and the approximation can be justified for signal to noise ratio (SNR) E _s/N₀ ≫ 1.5 dB     

长时延扩展水声信道的联合稀疏恢复估计

对具有长时延扩展的水声信道,传统的信道估计算法如最小二乘法将在大量零值抽头产生严重的估计噪声,导致估计性能下降,同时信道估计时所需的较高估计器阶数大大提高了运算复杂度。压缩感知信道估计方法可有效利用多径稀疏特性改善性能,但需采用较大的训练序列长度以保证稀疏恢复精度,由此导致额外的系统开销。利用水声信道多径稀疏结构在数据块间存在的相关性,建立基于分布式压缩感知的长时延水声信道联合稀疏模型,从而可利用同步正交匹配追踪算法进行联合重构,以进一步减小系统的训练序列开销,提高估计性能。最后通过仿真和海上实验验证了所提方法的有效性。     

Feedback equalization for fading dispersive channels

Data transmission through a slowly fading dispersive channel is considered. A receiver that linearly operates on both the received signal and reconstructed data is postulated. Assuming an absence of decision errors, the receiver is optimized for a minimum-mean-square-error criterion. Transfer functions are determined and superiority over nonfeedback receivers is indicated. The feedback receiver can be realized in a slowly varying unknown environment by means of an adaptive technique that requires neither test signals nor statistical estimation. The receiver will eliminate timing jitter and Doppler shifts. In addition, the receiver provides a time-diversity effect, as the receiver probability of error averaged over the fading statistics is lower in the presence of dispersion than in its absence.     

Layered space-time equalization for wireless MIMO systems

We investigate layered space-time equalization (LSTE) architectures for multiple-input multiple-output (MIMO) frequency-selective channels. At each stage or layer of detection, a MIMO delayed decision feedback sequence estimator (MIMO-DDFSE) is used to tentatively detect a group of selected data streams, among which a subgroup of data streams are output and are canceled from the received signals. With the proposed architectures, the numbers of the tentatively detected data streams and output data streams can be different at different LSTE stages, while the MIMO-DDFSE can also reduce to the special cases of multiple-input single-output decision feedback equalizer (MISO-DFE), MISO-DDFSE, and MIMO-DFE, allowing tradeoffs between performance and complexity. We also derive the equalizer coefficients, discuss timing recovery, and consider channel estimation. Simulation results demonstrate the performance of the proposed LSTE structures and the tradeoffs between performance and complexity of the multistage structure and the single-stage version. We also demonstrate the impact of imperfect channel estimation, imperfect interference cancellation, the number of receive antennas, filter length, and oversampling on performance.     

Estimation of frequency-selective CDMA channels with large possible delay and Doppler spreads

The problem of estimating channels with a large number of unknown coefficients is considered. A matching pursuit (MP) followed by cancellation (MPC) algorithm is presented. The algorithm consists of two steps. In the first step, a basic MP algorithm that identifies the strongest channel taps and successively cancels them is used. The second step of the algorithm uses the already identified channel taps to estimate the channel coefficients more accurately. The algorithm has several benefits: low complexity, significantly improved performance over conventional least squares (LS) in sparse channels, and handling of time-varying channels including carrier offsets. Methods to successfully terminate the MP step of the algorithm are presented and are shown to perform well. The statistical behavior of MPC is studied. The MPC estimator is found to achieve a performance close to the Cramer-Rao lower bound. Further, MPC is found to outperform conventional LS in terms of bit error rate when low training overhead is used.