IEEE Transactions on Signal Processing

Multiple-input multiple-output (MIMO) antenna systems employ spatial multiplexing to increase spectral efficiency or transmit diversity to improve link reliability. The performance of these signaling strategies is highly dependent on MIMO channel characteristics, which, in turn, depend on antenna height and spacing and richness of scattering. In practice, large antenna spacings are often required to achieve significant multiplexing or diversity gain. The use of dual-polarized antennas (polarization diversity) is a promising cost- and space-effective alternative, where two spatially separated uni-polarized antennas are replaced by a single antenna structure employing orthogonal polarizations. This paper investigates the performance of spatial multiplexing and transmit diversity (Alamouti (see IEEE J. Select. Areas Commun., vol.16, p.1451-58, Oct. 1998) scheme) in MIMO wireless systems employing dual-polarized antennas. In particular, we derive estimates for the uncoded average symbol error rate of spatial multiplexing and transmit diversity and identify channel conditions where the use of polarization diversity yields performance improvements. We show that while improvements in terms of symbol error rate of up to an order of magnitude are possible in the case of spatial multiplexing, the presence of polarization diversity generally incurs a performance loss for transmit diversity techniques. Finally, we provide simulation results to demonstrate that our estimates closely match the actual symbol error rates.

Blind detection of a desired user's signal in a multirate direct sequence code division multiple access (DS-CDMA) system [using either variable sequence length (VSL) or multicode (MC) access] is considered. A code-constrained inverse filter criterion (IFC)-based blind detector for equal-rate CDMA signals to detect a desired user's signal was presented by Tugnait and Li (2001). The IFC method exploits the higher order statistics of the data. In multirate CDMA systems, a high-rate user signal may be treated as the superposition of several virtual basic-rate signals. The code-constrained IFC-based detector may be used to detect a given basic-rate virtual signal. This, however, does not solve the problem of combining the detected virtual basic-rate signals to yield the original high-rate signal since the former may be delayed by different equalization delays, may be multiply extracted, and may be in different "order." In this paper, novel approaches combining the code-constrained IFC and a penalty function are developed to cope with this problem for VSL and MC multirate access methods. Global minima of the proposed cost functions are analyzed. Three illustrative simulation examples are presented, including an example where the proposed algorithms are compared with an existing subspace approach (and its modifications), a clairvoyant matched filter receiver, and a known channel linear minimum mean-square error (MMSE) receiver.

Dựa trên phương pháp không gian nhiễu tối thiểu (MNS) được giới thiệu trước đây trong bối cảnh nhận dạng kênh mù, không gian nhiễu tối thiểu tổng quát (GMNS) được đề xuất trong bài báo này cho xử lý mảng, mở rộng MNS liên quan đến việc chỉ có một số lượng cố định các đơn vị tính toán song song. Các thuật toán theo lô và thích ứng khác nhau sau đó được giới thiệu để tính toán nhanh và song song các không gian tín hiệu (chính) và nhiễu (phụ). Độ phức tạp tính toán của GMNS và độ chính xác ước lượng liên quan của nó được điều tra thông qua các thí nghiệm mô phỏng và một thí nghiệm thực tế trong thiên văn vô tuyến. Kết quả cho thấy GMNS đại diện cho một sự trao đổi tuyệt vời giữa lợi ích tính toán và độ chính xác ước lượng không gian, so với một số phương pháp không gian tiêu chuẩn.

We address the problem of polarimetric adaptive detection of range-spread targets in Gaussian noise with unknown covariance matrix. At the design stage, we model the target echo from each polarimetric channel as a deterministic signal known up to a scaling factor (possibly varying from cell to cell), which accounts for the polarimetric scattering properties of the target. We first show the failure of the generalized likelihood ratio test (GLRT) procedure to deal with this kind of problem, and thus, we propose a fully adaptive detector based on the method of sieves. We also derive the analytical expression for the probability of false alarm and show that the newly introduced receiver can be made bounded constant false alarm rate (CFAR). Finally, we present simulation results highlighting the performance gain that can be achieved by resorting to polarization diversity in conjunction with high resolution.

During the last decade, a comprehensive theory for optimum time-frequency (TF)-based detection has been developed. This was originally proposed in the continuous-time continuous-frequency case. This paper deals with detectors operating on discrete-time discrete-frequency Wigner distributions (WDs). The purpose is to discuss some existing definitions of this distribution within the context of TF-based detection and selecting those that do not affect the performance of the decision device with which they are associated. This question is of interest since there exist several approaches for discretizing the WD, sometimes resulting in a loss of fundamental properties. First, the discrete-time discrete-frequency formulations of optimum detection are investigated. Next, the problem of the design of TF-based detectors from training data, keeping in mind severe effects of the curse of dimensionality, is considered.

We consider the direction-finding problem in partly calibrated arrays composed of several calibrated and identically oriented (but possibly nonidentical) subarrays that are displaced by unknown (and possibly time-varying) vector translations. A new search-free eigenstructure-based direction-finding approach is proposed for such class of sensor arrays. It is referred to as the rank-reduction (RARE) estimator and enjoys simple implementation that entails computing the eigendecomposition of the sample array covariance matrix and polynomial rooting. Closed-form expressions for the deterministic Cramer-Rao bounds (CRBs) on direction-of-arrival (DOA) estimation for the considered class of sensor arrays are derived. Comparison of these expressions with simulation results show that the finite-sample performance of RARE algorithms in both time-invariant and time-varying array cases is close to the corresponding bounds. Moreover, comparisons of the derived CRBs with the well-known bounds for the fully calibrated time-invariant array case help to discover several interesting properties of DOA estimation in partly calibrated and time-varying arrays.

Smart antenna techniques at the base station can dramatically improve the performance of the mobile radio system by employing spatial filtering. The design of a fully spatial signal processor using rectangular array configuration is proposed. Two-dimensional (2-D) spatial filters that can be implemented by microstrip technology are capable of filtering the received signal in the angular domain as well as the frequency domain. Furthermore, it has wideband properties and, hence, eliminates the requirement of different antenna spacing for applications including various carrier frequencies. The desired frequency selectivity of the smart antenna can be combined with compensation of the undesired frequency performance of a single antenna element, and the result is quite satisfactory for practical implementation. In addition, if the elements of the array are not perfectly omnidirectional or frequency independent, we can compensate for these deficiencies in the design algorithm. Two different algorithms for calculating the real-valued weights of the antenna elements are proposed. The first algorithm is more complex but leads to sharper beams and controlled performance. The second method is simpler but has wider beam and lower fractional bandwidth. Some computer simulation results demonstrating the directional beam patterns of the designed beamformers are also presented.

This paper presents a general framework for space-time codes (STCs) that encompasses a number of previously proposed STC schemes as special cases. The STCs considered are block codes that employ arbitrary redundant linear precoding of a given data sequence together with embedded training symbols, if any. The redundancy introduced by the linear precoding imposes structure on the received data that under certain conditions can be exploited for blind or semi-blind estimation of the transmitted sequence, a linear receiver that recovers the sequence, or both simultaneously. Algorithms based on this observation are developed for the single-user flat-fading case and then extended to handle multiple users, frequency-selective fading, as well as situations where the channel is rank deficient, or there are fewer receive than transmit antennas.