We propose a dimension reduction algorithm for the receiver of the downlink of direct-sequence code-division multiple access (DS-CDMA) systems in which both the transmitters and the receivers employ antenna arrays of multiple elements. To estimate the high order channel parameters, we develop a layered architecture using dimension-reduced parameter estimation algorithms to estimate the frequency-selective multipath channels. In the proposed architecture, to exploit the space-time geometric characteristics of multipath channels, spatial beamformers and constrained (or unconstrained) temporal filters are adopted for clustered-multipath grouping and path isolation. In conjunction with the multiple access interference (MAI) suppression techniques, the proposed architecture jointly estimates the direction of arrivals, propagation delays, and fading amplitudes of the downlink fading multipaths. With the outputs of the proposed architecture, the signals of interest can then be naturally detected by using path-wise maximum ratio combining. Compared to the traditional techniques, such as the Joint-Angle-and-Delay-Estimation (JADE) algorithm for DOA-delay joint estimation and the space-time minimum mean square error (ST-MMSE) algorithm for signal detection, computer simulations show that the proposed algorithm substantially mitigate the computational complexity at the expense of only slight performance degradation.

This paper presents a semi-blind algorithm for multiuser interference cancellation and fading amplitude estimation for downlink MIMO DS-CDMA systems with multipath fading channels. Taking advantage of the space-time information of the parametric multipath channel, the proposed algorithm first uses a space-time channel decoupler to suppress multiuser interference and then decomposes the channel into a set of parallel subchannels each containing the signal of the desired user on an individual multipath. Two criteria, the complementary orthogonal projection (COP) and the minimum variance distortionless response (MVDR), are employed by the space-time decoupler to achieve interference suppression and signal separation. The fading amplitudes can then be estimated from the eigen space of the output of the space-time channel decoupler. It follows that the signal of interest can be maximally combined in a pathwise manner and then differentially decoded.

Signals received at the interrogator of an RFID system always suffer from various kinds of channel deformation factors, such as the path loss of the wireless channel, insufficient channel bandwidth resulted from the multipath propagation, and the carrier frequency offset between tags and interrogators. In this paper we proposed a novel Viterbi-based algorithm for joint detection of data sequence and compensation of distorted signal waveform. With the assumption that the transmission clock is exactly synchronized at the reader, the proposed algorithm takes advantage of the structured data-encoded waveform to represent the modulation scheme of the RFID system as a trellis diagram and then the Viterbi algorithm is applicable to perform data sequence estimation. Furthermore, to compensate the distorted symbol waveform, the proposed Jiggle-Viterbi algorithm generates two substates, each corresponding to a variant structure waveform with adjustable temporal support, so that the symbol waveform deformation can be compensated and therefore yield a significant better performance in terms of bit error rate. Computer simulations shows that even in the presence of a moderate carrier frequency offset, the proposed approach can work out with an acceptable accuracy on data sequence detection.

Multiple-input-multiple-output (MIMO) wireless systems can not always have full spatial multiplexing gain due to the channel correlation problem caused by various factors such as the coupled antenna elements, and the key-hole effect of the propagation environment. In this paper, we proposed a channel reconfiguration technique to combat the rank deficiency problem of the involved MIMO wireless channels that can not afford high-order multiplexing gains. In the proposed approach, each mobile station can simultaneously receive several independent data streams from multiple base stations through a set of MMSE-based receive beamformers to suppress the multiple access interferences. Making use of the receive beamforming, which virtually produce the effect of a single antenna at each receive mobile, makes the transmit base station possible to reconfigure the MIMO downlink channel and then pre-cancel the co-channel interferences. The proposed signal processing mechanism that iteratively optimized the MMSE receive weights and the transmit precoders, which brings the reconfigured MIMO system about the high data throughput seen only with indoor MIMO systems having rich wireless channels. It is shown that as compared to the conventional MIMO system, the M4 system can achieve a significantly higher capacity which is proportional to the number of the linked base stations.

This paper proposes two space-time joint channel parameter estimation and signal detection algorithms for downlink DS-CDMA systems with multiple-input-multiple-output (MIMO) wireless multipath fading channels. The proposed algorithms initially use the space-time MUSIC to estimate the DOA-delays of the multipath channel. Based on these estimated DOA-delays, a space-time channel decoupler is developed to decompose the multipath downlink channel into a set of independent parallel subchannels. The fading amplitudes of the multipath can then be estimated from the eigen space of the output of the space-time channel decoupler. With these estimated channel parameters, signal detection is carried out by a maximal ratio combiner on a pathwise basis. Computer simulations show that the proposed algorithms outperform the conventional space-time RAKE receiver while having the similar performance compared with the space-time minimum mean square error receiver.

A blind joint parametric channel estimation and non-coherent data detection algorithm is proposed for the downlink of an orthogonal-frequency-division-multiplexing code-division-multiple-access (OFDM-CDMA) system with multiple-input-multiple-output (MIMO) antenna arrays. To reduce the computational complexity, we first develop a tree-structured algorithm to estimate high dimensional parameters predominantly describing the involved multipath channels by employing several stages of low dimensional parameter estimation algorithms. In the tree structure, to exploit the space-time distribution of the receive multipath signals, spatial beamformers and spectral filters are adopted for clustered-multipath grouping and path isolation. In conjunction with the multiple access interference (MAI) suppression techniques, the proposed tree architecture algorithm jointly estimates the direction of arrivals, propagation delays, carrier frequency offsets and fading amplitudes of the downlink wireless channels in a MIMO OFDM-CDMA system. With the outputs of the tree architecture, the signals of interest can then be naturally detected with a path-wise maximum ratio combining scheme.

For advanced mobile communication systems that adopt orthogonal frequency-division multiple access (OFDMA) technologies, intercarrier interference (ICI) significantly degrades performance when mobility is high. Standard specifications and concerns about complexity demand low-cost methods with deployment readiness and decent performance. In this paper, novel zero forcing (ZF) and minimum mean-square error (MMSE) equalizers based on per-subcarrier adaptive (PSA) processing and perturbation-based (PB) approximation are introduced. The proposed equalizers strike a good balance between implementation cost and performance; therefore they are especially suitable for OFDMA downlink receivers. Theoretical analysis and simulations are provided to verify our claims.