Jiunn-Tsair Chen

TST-MUSIC for joint DOA-delay estimation

A multiple signal classification (MUSIC)-based approach known as the time-space-time MUSIC (TST-MUSIC) is proposed to jointly estimate the directions of arrival (DOAs) and the propagation delays of a wireless multiray channel. The MUSIC algorithm for the DOA estimation is referred to as the spatial-MUSIC (S-MUSIC) algorithm. On the other hand, the temporal-MUSIC (T-MUSIC), which estimates the propagation delays, is introduced as well. Making use of the space-time characteristics of the multiray channel, the proposed algorithm-in a tree structure-combines the techniques of temporal filtering and of spatial beamforming with three one-dimensional (1-D) MUSIC algorithms, i.e., one S-MUSIC and two T-MUSIC algorithms. The incoming rays are thus grouped, isolated, and estimated. At the same time, the pairing of the estimated DOAs and delays is automatically determined. Furthermore, the proposed approach can resolve the incoming rays with very close DOAs or delays, and the number of antennas required by the TST-MUSIC algorithm can be made less than that of the incoming rays.

A two-stage hybrid approach for CCI/ISI reduction with space-time processing

We present a hybrid approach for separate cochannel interference (CCI) reduction and intersymbol interference (ISI) equalization in a slow Rayleigh fading channel. In this hybrid approach, a space-time filter is designed to maximize signal-to-interference-plus-noise ratio (SINR) by jointly optimizing the weight vector and the modified channel vector. A Viterbi equalizer then follows to equalize ISI and demodulate data symbols without noise enhancement. We derive an eigenvector solution for the joint optimization of the weight vector and the modified channel vector. Simulation results show good performance even at low carrier-to-interference-ratio (CIR).

Joint Polynomial and Look-Up-Table Predistortion Power Amplifier Linearization

Digital predistortion at baseband is an efficient and low-cost method for the linearization of a power amplifier (PA) in a wireless system employing a nonconstant-envelop modulation scheme, so as to reduce the adjacent channel interference. The polynomial and the look-up table (LUT) predistortion schemes are two commonly used approaches. However, in each of the two approaches, to reach a satisfactory adjacent channel power ratio (ACPR) in the PA output signal, people usually end up with a complex system having the involved algorithms converge rather slowly. In this brief, we propose a low-complexity joint-polynomial-and-LUT predistortion PA linearizer, where the two mutually dependent predistortion schemes can skillfully help each other. Simulation results show that the proposed joint linearizer can reduce the algorithm convergence time while achieving an excellent ACPR

FSF MUSIC for Joint DOA and Frequency Estimation and Its Performance Analysis

In this paper, we present a tree-structured frequency-space-frequency (FSF) multiple signal classification (MUSIC)-based algorithm for joint estimation of the directions of arrival (DOAs) and frequencies in wireless communication systems. The proposed approach is a novel twist of parameter estimation and filtering processes, in which two one-dimensional (1-D) frequency (F)- and one 1-D space (S)-MUSIC algorithms are employed-in a tree structure-to estimate the DOAs and frequencies, respectively. In between every other MUSIC algorithm, a temporal filtering process or a spatial beamforming process, implemented by a set of complementary projection matrices, is incorporated to partition the incoming rays to enhance the estimation accuracy, so that the incoming rays can be well resolved even with very close DOAs or frequencies, using the 1-D MUSIC algorithms. Also, with such a tree-structured estimation scheme, the estimated DOAs and frequencies are automatically paired without extra computational overhead. Furthermore, some statistical analyses of the undesired residue signals propagating between the 1-D MUSIC algorithms and the mean square errors of the parameter estimates are derived to provide further insights into the proposed approach. Simulations show that the new approach can provide comparable performance, but with reduced complexity compared with previous works, and that there is a close match between the derived analytic expressions and simulation results

The optimal RLS parameter tracking algorithm for a power amplifier feed-forward linearizer

Digital signal processing (DSP) techniques have been proposed in recent years to adaptively track the control parameters of a power amplifier (PA) feed-forward linearizer. In most of the propositions, gradient-based searching algorithms are applied to the parameter tracking. In this paper, we propose an optimal RLS (recursive least square) parameter tracking algorithm, which significantly accelerates the convergence speed and eliminates the gradient noise. There exists two problems for the RLS algorithm. First, the least square solution is not the optimal solution because of the nonlinearity of the PA. Second, the vector modulator (VM) which introduces the control parameters into the linearizer circuit may not be accurate enough to provide a precise power gain and phase shift calculated by the DSP. We solve both problems, respectively, by rearranging the circuit components and by constraining the VM characteristics. We also present simulation results to verify the performance improvement of the proposed algorithm.

Multichannel maximum-likelihood sequence estimation (MLSE) equalizer for GSM using a parametric channel model

We propose a novel algorithm for the maximum-likelihood sequence estimation (MLSE) equalizer for the Global System for Mobile Communications (GSM) system. Specifically, we use a parametric model for the channel, along with a modified phase pulse-shaping function of Gaussian minimum shift keying (GMSK) modulation to obtain the modified Viterbi equalizer which we refer to as the parametric channel-Viterbi equalizer (PC-VE). In contrast to the conventional Viterbi equalizer with a finite impulse response (FIR) channel description, the PC-VE avoids the linear approximation error. The PC-VE also has a lower computational complexity if the number of the propagation paths is less than the number of the FIR channel taps multiplied by the number of antennas. The proposed algorithm is applicable to both single and multiantenna receivers. An analytical expression for the BER as a function of the SNR, path delays, and path DOAs has been derived. Some simulation results that illustrate the performance of the proposed algorithm are presented.

A novel indoor RSS-based position location algorithm using factor graphs

A low-complexity and accurate receive-signal strength (RSS)-based algorithm is proposed to estimate a target location. To achieve the aim of low complexity, a local linearization technique based on the local linearity in the surface of power decay profile (PDP), established by training logarithmic RSS measurements and collected from each individual access point (AP), was devised. To achieve a near-optimum solution, the stochastic properties of measurement errors and the reliability of the measurement data are introduced into the factor graph framework. Numerical experiments show that the proposed algorithm not only achieves a near maximum likelihood (ML) solution based on training RSS measurements, but also enjoys low complexity.

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

Dynamically optimum lookup-table spacing for power amplifier predistortion linearization

The lookup-table-based digital adaptive predistortion (DAPD-LUT) approaches are low cost and effective for power amplifier (PA) linearization in wireless applications. However, most existing DAPD-LUT schemes are sub-optimum because they adopt uniformly spaced LUTs regardless of the system state information (SSI), i.e., the PA characteristics and the input signal statistics. Other existing DAPD-LUT schemes assume either full or partial knowledge of the SSI to optimize and then to freeze the LUT spacing. Without prior knowledge of the SSI, we propose an SSI-learning low-complexity procedure to optimize the LUT spacing for a DAPD-LUT scheme. The proposed procedure is capable of online adapting the LUT spacing for PAs with various nonlinear characteristics, for input signals with various statistics, and for wireless environments with various time-varying properties.

Multi-channel MLSE equalizer with parametric FIR channel identification

We propose a parametric finite impulse response (FIR) channel identification algorithm, apply the algorithm to a multichannel maximum likelihood sequential estimation (MLSE) equalizer using multiple antennas, and investigate the improvement in the overall bit error rate (BER) performance. By exploring the structure of the specular multipath channels, we are able to reduce the number of channel parameters to provide a better channel estimate for the MLSE equalizer. The analytic BER lower bounds of the proposed algorithm as well as those of several other conventional MLSE algorithms in the specular multipath Rayleigh-fading channels are derived. In the derivation, we consider the channel mismatch caused by the additive Gaussian noise and the finite-length channel approximation error. A handy-to-use simplified BER lower bound is also derived. Simulation results that illustrate the BER performance of the proposed algorithm in the global system for mobile communications (GSM) system are presented and compared to the analytic lower bounds.