In this paper, we present a new approach for the design of partially adaptive broadband beamformers with the generalized sidelobe canceller (GSC) as an underlying structure. The approach designs the blocking matrix involved by utilizing a set of P-regular, M-band wavelet filters, whose vanishing moment property is shown to meet the requirement of a blocking matrix in the GSC structure. Furthermore, basing on the subband decomposition property of these wavelet filters, we introduce a new dynamic subband selection scheme succeeding the blocking matrix. The scheme only retains the principal subband components of the blocking matrix outputs based on a prescribed statistical hypothesis test and thus further reduces the dimension of weights in adaptive processing. As such, the overall computational complexity, which is mainly dictated by the dimension of adaptive weights, is substantially reduced. The furnished simulations show that this new approach offers comparable performance as the existing fully adaptive beamformers but with reduced computations.

A one dimensional (1-D) based tree structure algorithm is proposed for estimating the 2D-DOAs of the signals impinging on a uniform rectangular array. The key idea of the proposed algorithm is to successively utilize the 1-D MUSIC algorithm several times, in tree structure, to estimate the azimuth and the elevation angles independently. Subspace projectors are exploited in conjunction with the 1-D MUSIC algorithms to decompose the received signal into several signals each coordinated by its own 2D-DOA. The pairing of the azimuth estimates and the associated elevation estimates is naturally determined due to the tree structure of the algorithm.

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.

The design of the finite impulse response (FIR) notch filter with controlled null width is expressed as a derivatively contrained quadratic optimization problem. The problem is transformed into an unconstrained one by choosing a null matrix orthogonal to the derivative constraint matrix. In this paper, subband decomposition using wavelet filters is employed to construct the null matrix. Taking advantage of the vanishing moment property of the wavelet filters, the proposed method can adjust the null width of the notch filter for eliminating the intractable iterference by controlling the regularity of the wavelet filters. Simulation results show that the new method can offer comparable performance as those of the existing full-rank-based ones and thus provides a promising alternative to the existing works.

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.

We propose an innovative and practically attainable downlink multi-cell MIMO system with distributed transmit beamforming design. The proposed system is referred to as the MIMO-MAP system which is aimed to mitigate the rank deficiency problem of those MIMO wireless channels that can not support high-order multiplexing gains. In the MIMO-MAP system, each mobile station is allowed to receive several independent data streams from multiple access points at the same time and the same frequency. To do this, a set of noise-subspace-based receive beamformers are employed to suppress the interference among the data streams from different access points. On the other hand, if we consider each receive beamformer as part of its associated wireless channel, we virtually reduce the antenna array at each receive mobile station to a single antenna. With this arrangement, we may have the transmit signal dimension high enough to pre-cancel the inter-stream-interferences at each transmit access point. As a result, the MIMO-MAP channel can be decomposed into a large number of independent subchannels which significantly increase the channel capacity.

Conventional RFID interrogators use symbol-by-symbol-based detectors such as the matched filter and the edge detector for signal detection which do not sufficiently exploit the structure of the data-encoded waveforms. In this paper we propose a Viterbi-based algorithm to detect the data sequence of the RFID systems using the EPC-Global Generation-2 standard. By decomposing the associated data-encoded waveform on a half-cycle basis, the proposed approach first transfer the representation of the data-encoding scheme to a trellis diagram and thus leads to the application of the Viterbi algorithm for data sequence estimation. Also, different from the traditional Viterbi algorithm using correlation coefficient as the branch metrics, the proposed algorithm uses the absolute correlation coefficient as our branch metric which can exactly save the computational complexity of the Viterbi algorithm up to 50 percent. As compared to conventional approaches, the proposed algorithm can significantly improve the system performance due to its full exploitation of the baseband signal structure.

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 study proposes an improved per-survivor-processing (PSP) scheme to tackle the phase error issue in the convolutionally coded OFDM systems. The proposed approach takes advantage of the trellis structure of the convolutional codes to compensate the symbol-time-offset (STO) caused phase error in frequency domain. Unlike the traditional PSP scheme which simply estimates the phase error by using a state-based horizontal process, the proposed approach develops an extra state-wise vertical process which selects the most likely phase estimate as the survival phase in each trellis stage and then accordingly align the phase of all states to this survival phase before moving to next trellis stage of the PSP scheme. With the vertical process, the resultant phase estimate is more reliable than that of the conventional PSP scheme and hence improve the accuracy in data decoding. Computer simulations confirm the validity of the proposed approach.

In this study, a precoding scheme based on QR-decomposition is proposed for mitigating the inter-carrier-interference (ICI) in orthogonal-frequency-division-multiplexing (OFDM) systems. The proposed approach first subjects the ICI matrix to QR decomposition so that the ICI effect is transformed into its spectrally causal equivalent. With this causality, the precoding can then be conducted based on the resultant spectrally causal matrix. In addition, by using the stationary property of the ICI factors, in conjunction with zero padding, we implement the QR-based precoding in a segmentation manner which can significantly alleviate the computational complexity imposed by QR decomposition while eliminating ICI within each segment. This study also analyzes the residue interference power induced by the segmentation. The residue interference power is then accordingly used to determine the order of zero padding. Computer simulations support the validity of the proposed approach.

In this paper, we propose an Estimation of Signal Parameter via Rotational Invariance Techniques (ESPRIT) based algorithm for estimating the two-dimensional-direction-of-arrivals (2D-DOA) of signals impinging on a uniform rectangular array (URA). The basic idea of the proposed algorithm is to successively apply two rounds of one-dimensional ESPRIT (1D-ESPRIT) algorithm for 2D-DOA estimation. The first round 1D-ESPRIT is applied on columns of the URA whereas the other round 1D-ESPRIT is on the rows of the URA. In between, a grouping technique is developed to produces signal groups each containing signals with distinguishable spatial signatures. The grouping technique is performed by using the subspace projection method where the needed spatial information is provided by the first round 1D-ESPRIT algorithm. Computer simulations show that, in addition to having significantly reduced computational complexity, the proposed algorithm possesses better estimation accuracy as compared to the conventional 2D-ESPRIT algorithm.

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.

This paper presents a wavelet-based approach for the design of the finite impulse response (FIR) notch filter with controlled null width. The M-band P-regular wavelet filters are employed to constitute the null space of the derivative constraint matrix. Taking advantage of the vanishing moment property of the wavelet filters, the proposed method controls the null width of the notch filter by adjusting the regularity of the employed wavelet filters. Besides, the selection of large number of bands of the wavelet filters can effectively reduce the minimum mean square error and thus improve the performance of the notch filter. Computer simulations show that, in addition to possessing lower computational complexity, the proposed reduced-rank method has similar frequency response compared to those of the full-rank-based techniques.

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.

In this study, we propose a one dimensional (1D) based successive generalized sidelobe canceller (GSC) structure for the implementation of 2D adaptive beamformers using a uniform rectangular antenna array (URA). The proposed approach takes advantage of the URA feature that the 2D spatial signature of the receive signal can be decomposed into an outer product of two 1D spatial signatures. The 1D spatial signatures lie in the column and the row spaces of the receive signal matrix, respectively. It follows that the interferers can be successively eliminated by two rounds of 1D-based GSC structure. As compared to the conventional 2D-GSC structure, computer simulations show that in addition to having significantly low computational complexity, the proposed adaptive approach possesses higher convergence rate.