Yeong-Cheng Wang

Network-side mobile position location using factor graphs

A low-complexity high-accuracy algorithm is proposed to estimate the location of a target MS based on network-side time-of-arrival (TOA) measurements. Under a factor graph framework, the proposed algorithm first constructs a graphical model for the mobile position location problem by dividing the problem into many mutually-interactive local constraints. Each local constraint is enforced by a separate local processing unit. Efficient exchange of soft-information among local processing units in the mobile switching center (MSC) then iteratively purifies the estimate of the MS location. Numerical results show that the proposed algorithm not only enjoys low complexity, suitable for integrated-circuit implementation, but it is also able to achieve performance very close to the optimum achievable solution accuracy, the maximum likelihood (ML) solution accuracy

Mobile position location using factor graphs

Making use of the time-of-arrival measurements and their stochastic properties, we propose a low-complexity high-accuracy algorithm to estimate the location of a target mobile station (MS). Under a factor graph framework, in the proposed algorithm, soft-information is efficiently exchanged among local processing units to iteratively purify the estimate of the MS location. Numerical results show that the proposed algorithm not only enjoys advantages of low complexity, suitable for integrated-circuit implementation, but it is also able to achieve performance very close to the optimum achievable bound, the maximum-likelihood bound.

Joint polynomial and look-up-table power amplifier linearization scheme

Power amplification is one of the crucial functions in wireless communications systems. Unfortunately, power amplifiers often encounter the problem of severe nonlinear distortion. This paper studies two types of predistortion linearization schemes for power amplifiers: polynomial and look-up-table (LUT). With limited complexity in both linearization schemes, the polynomial scheme suffers curve-fitting distortion, while the LUT scheme suffers granular distortion, i.e., distortion at those parts of a power amplifier signal where its input amplitudes are between the values specified by the LUT entries. To reach adjacent channel power ratio (ACPR) of up to 60 dBc or even higher for signals at a power amplifier output usually requires a very complicated system with the involved algorithms converging rather slowly. However, the nonlinear distortions remaining in the polynomial scheme and in the LUT scheme are quite different. Therefore, the two linearization schemes are capable of canceling the remaining distortion for each other. With this in mind, we propose a joint polynomial and LUT power amplifier linearization scheme where the polynomial scheme effectively minimizes the granular distortion that the LUT scheme might suffer. Baseband simulations are conducted to justify the proposed joint linearization scheme.

An adaptive spatio-temporal coding scheme for indoor wireless communication

Systems that employ multiple antennas in both the transmitter and the receiver of a wireless system have been shown to promise extraordinary spectral efficiency. With full channel knowledge at the transmitter and receiver, Raleigh and Cioffi (1998) proposed a spatio-temporal coding scheme, discrete matrix multitone (DMMT), to achieve asymptotically optimum multiple-input-multiple-output (MIMO) channel capacity. The DMMT can be regarded as an extension of the discrete multitone for a digital subscriber lines (DSL) system to the MIMO wireless application. However, the DMMT is basically impracticable in nonstationary wireless environments due to its high-computational complexity. Exploring second-order statistics, we develop an efficient adaptive blind coding scheme for a high-capacity time-division duplexing (TDD) system with slow time-varying frequency-selective MIMO channels. With this method, neither a training sequence nor feedback of channel information is required in the proposed blind approach. Besides, the computational complexity of the proposed scheme is significantly lower than that of the coding scheme described by Raleigh and Cioffi. Simulation results show that the proposed architecture works efficiently in indoor wireless local area network applications.

Low-complexity channel-adapted space-time coding scheme for frequency-selective wireless MIMO channels

By exploiting the wireless multiple-input multiple-output (MIMO) channel structure, a brand new space-time code design criterion is derived. Based on the new criterion, we propose one low-complexity channel-adapted space-time (CAST) coding scheme, where trade-offs among codeword error rate, data throughput, and computational complexity are very flexible. Simulation results confirm that, in the frequency-selective MIMO channels, the CAST coding scheme can perform significantly better than the existing space-time codes, e.g., Alamouti space-time orthogonal code.

Structures of space-time codes and multipath MIMO channels

In a wireless system with multipath multiple-input multiple-output (MIMO) channels using antenna arrays, the delay spread of the multipaths results in intersymbol interference (ISI) and channel frequency selectivity. In contrast with the channel frequency selectivity, spatial gains at the multipath angles also naturally result in channel angle selectivity. Based on the channel selectivity structures characterized by the path delays and the path directions-of-departure/arrival, we seek new insights into the matching of space-time codes and multipath MIMO channels in their angle-frequency (AF) structures.

Structure-based water-filling algorithm in multipath MIMO channels

Recent advances in information theory show that employing multiple antennas at both sides of a wireless channel promises enormous capacity potential. With perfect knowledge of channel state information (CSI) at the transmitter, eigen-beamforming is the optimal coding scheme to exploit this potential. However, in nonstationary wireless environments, high complexity on multiple-input-multiple-output (MIMO) channel tracking and large amounts of CSI feedback render such an approach impractical. By exploiting the wireless multipath channel structure characterized by the path delays and the path directions-of-departure/arrival, we propose a new space-time transmit scheme which employs a structure-based water-filling algorithm.

Blind joint channel estimation and signal decoding for systems with time-varying Rayleigh-fading channels

This paper proposes a wireless system with a blind receiver which jointly performs noncoherent channel estimation and serially-concatenated turbo code decoding over fast time-varying Rayleigh-fading channels. The low complexity blind receiver consists of two parts: 1) a Kalman filter as its channel estimation part and 2) two decoders, including a differential decoder and a convolutional decoder, as its signal decoding part. With various soft information, calculated in the maximum likelihood sense, iteratively passed around between the channel estimator and the signal decoder, the system is expected to hopefully approach the optimal performance. Note that, with no training data in the proposed system, it is impossible for the Kalman filter to avoid the CSI (channel state information) phase ambiguity problem, which can be perfectly taken care of by the differential decoder. Computer simulations confirm that the proposed system exhibits robustness against fast time-variation of Rayleigh-fading channels.

New design criteria of space-time codes for frequency-selective multipath wireless channels

In a single-input-single-output (SISO) system, signals are modulated to have a band-pass structure in the frequency domain in order to pass through a channel with a bandpass frequency response. Similarly, in a multiple-input-multiple-output (MIMO) system with multipath wireless channels, signals radiated from the multiple transmit antennas can be processed to form beams in order to have the spatial structure to pass through the wireless channel along the multipaths. Analogous to the frequency response, a natural angle response is formed by the multipath angles. In this paper, by jointly exploring the angle and the frequency structures of the space-time codes and of the space-time channels, novel space-time codes design criteria at moderate signals-to-noise ratios are proposed. New space-time trellis codes are identified through computer searches to justify the new criteria. Simulation results show that these codes have superior performance over the existing codes in the corresponding frequency-selective channels.

Low-complexity channel-adapted space-time coding schemes for frequency-selective wireless MIMO channels

By exploiting the wireless MIMO (multiple input multiple output) channel structure, a brand new space-time code design criterion is derived. Based on the new criterion, we propose two low-complexity channel-adapted space-time (CAST) coding schemes, where trade-offs among codeword error rate, data throughput and computational complexity are very flexible. Simulation results confirm that, in frequency-selective MIMO channels, the CAST coding schemes can perform significantly better than existing space-time codes, e.g., Alamouti space-time orthogonal code.