Daniel N. Liu

Multi-antenna testbeds for research and education in wireless communications

Wireless communication systems present unique challenges and trade-offs at various levels of the system design process. Since a variety of performance measures are important in wireless communications, a family of testbeds becomes essential to validate the gains reported by the theory. Wireless testbeds also play a very important role in academia for training students and enabling research. In this article we discuss a classification scheme for wireless testbeds and present an example of the testbeds developed at UCLA for each of these cases. We present the unique capabilities of these testbeds, provide the results of the experiments, and discuss the role they play in an educational environment.

Iterative map equalization and decoding in wireless mobile coded OFDM

Orthogonal frequency division multiplexing (OFDM) system suffers extra performance degradation in fast fading channels due to intercarrier interference (ICI). Combining frequency domain equalization and bit-interleaved coded modulation (BICM), the iterative receiver is able to harvest both temporal and frequency diversity. Realizing that ICI channels are intrinsically ISI channels, this paper proposes a soft-in soft-out (SISO) maximum a posteriori (MAP) equalizer by extending Ungerboecks maximum likelihood sequence estimator (MLSE) formulation to ICI channels. The SISO MAP equalizer employs BCJR algorithm and computes the bit log-likelihood ratios (LLR) for the entire received sequence by efficiently constructing a trellis that takes into account of the ICI channel structure. A reduced state (RS) formulation of the SISO MAP equalizer which provides good performance/complexity tradeoff is also described. Utilizing the fact that ICI energy is clustered in adjacent subcarriers, frequency domain equalization is made localized. This paper further proposes two computational efficient linear minimum mean square error (LMMSE) based equalization methods: recursive q-tap SIC-LMMSE equalizer and recursive Sliding-Window (SW) SIC-LMMSE equalizer respectively. Simulations results demonstrate that the iterative SISO RS-MAP equalizer achieves the performance of no ICI with normalized Doppler frequency fdTs up to 20.46% in realistic mobile WiMAX environment.

Low Complexity Affine MMSE detector for Iterative Detection-Decoding MIMO OFDM system

Iterative turbo processing between detection and decoding shows near-capacity performance on a multiple-antenna system. Combining iterative processing with optimum front-end detection is particularly challenging because the front-end maximum a posteriori (MAP) algorithm has a computational complexity that is exponential in the throughput. Sub-optimum detector such as the soft interference cancellation linear minimum mean square error (SIC-LMMSE) detector with near front-end MAP performance has been proposed. The asymptotic computational complexity of SIC-LMMSE remains O(nt2nr+ntnr3+ntMc2Mc) per detection-decoding cycle where nt is number of transmit antenna, nr is number of receive antenna, and Mc is modulation size. A lower complexity detector is the hard interference cancellation LMMSE (HIC-LMMSE) detector. HIC-LMMSE has asymptotic complexity of O(nt2nr+ntMc2Mc)but suffers exta performance degradation. In this paper, we introduce a frontend detection algorithm that achieves asymptotic computational complexity of O(ntMc2Mc). Simulation results demonstrate that the proposed low complexity detection algorithm offers exactly same performance as their full complexity counterpart in an iterative receiver while being computational more efficient.

Field test results for space-time coding

Multiple antenna radios are recently the subject of much research due to the significant improvements they offer in throughput and reliability in wireless communications. Research in the field of space-time coding has led to the design of modulation techniques offering improved performance. Their performance, although promising in simulations, needs to be studied in real wireless channels due to the inability to accurately model all possible wireless channel conditions that might be seen in practice. With this motivation, a range of experiments were conducted to measure the performance of some of the well-known space-time codes in literature over real channels and under implementation impairments. This paper discusses the testbed setup for the experiments and present the results of field trials conducted at the University of California, Los Angeles.

Low complexity linear MMSE detector with recursive update algorithm for iterative detection-decoding MIMO OFDM system

Iterative turbo processing between detection and decoding shows near-capacity performance on a multiple-antenna system. Combining iterative processing with optimum front-end detection is particularly challenging because the front-end maximum a posteriori (MAP) algorithm has a computational complexity that is exponential in the throughput. Sub-optimum detector such as the soft interference cancellation linear minimum mean square error (SIC-LMMSE) detector with near front-end MAP performance has been proposed. The asymptotic computational complexity of SIC-LMMSE remains O(nE2_tn_r + n_tnE3 _r + n_tM_c2^M _c) per detection-decoding cycle where n_t is number of transmit antenna, n_r is number of receive antenna, and mc is modulation size. A lower complexity detector is the hard interference cancellation LMMSE (HIC-LMMSE) detector. HIC-LMMSE has asymptotic complexity of O(nE2_tn_r + n_tM_c2^M _c) but suffers extra performance degradation. In this paper, we introduce a low complexity front-end detection algorithm that not only achieves asymptotic computational complexity of O(nE2_tn_r + n_tnE3_r[Gamma (beta)] + n_tM_c2 ^M _c) where [Gamma (beta) is a function with discrete output {-1,2,3, ...,n_t}. Simulation results demonstrate that the proposed low complexity detection algorithm offers exactly same performance as its full complexity counterpart in an iterative receiver while being computational more efficient

Joint turbo channel estimation and data recovery in fast fading mobile coded OFDM

Orthogonal frequency division multiplexing (OFDM) systems suffer performance degradation in fast fading channels due to intercarrier interference (ICI). Combining frequency domain equalization and bit-interleaved coded modulation (BICM), the iterative receiver is able to harvest both temporal and frequency diversity. In order to perform coherent detection and estimation, channel state information (CSI) is critical. Conventional frequency domain channel estimation (CE) methods have an irreducible error floor at high normalized Doppler frequency fdTs, since ICI corrupts the orthogonality among subcarriers. Considering that the fast time-varying channel is also a source of temporal diversity, CE ought to take place in the pre-FFT time domain. With soft a priori information about the data symbols becomes available, this paper proposes a turbo channel estimator (TCE) structure which provides a way to consistently improve the bit error rate (BER). The complexity of TCE is further reduced by completely avoiding matrix inversion. Simulation results demonstrate that the PSAM system with TCE achieves no ICI with normalized Doppler frequency fdTs up to 20.46% with realistic mobile WiMAX channel environment.

Recursive LMMSE-based Equalization in Wireless Mobile Coded OFDM

Orthogonal frequency division multiplexing (OFDM) system suffers extra performance degradation in fast fading channels due to intercarrier interference (ICI). Combining frequency domain equalization and bit-interleaved coded modulation (BICM), the iterative receiver is able to harvest both temporal and frequency diversity. Using the fact that ICI energy is clustered in adjacent subcarriers, frequency domain equalization is made localized. A computational efficient recursive q-tap SIC-LMMSE equalizer is derived. Comparing to conventional method which requires matrix inversion using O(32 ldr q2K2), where K is number of subcarriers, the proposed recursive equalizer only uses O(20 ldr qK2) but without sacrificing performance.

Recursive Sliding-Window LMMSE-Based Equalization in Wireless Mobile Coded OFDM

Orthogonal frequency division multiplexing (OFDM) system suffers extra performance degradation in fast fading channels due to intercarrier interference (ICI). Combining frequency domain equalization and bit-interleaved coded modulation (BICM), the iterative receiver is able to harvest both temporal and frequency diversity. Using the fact that ICI energy is clustered in adjacent subcarriers, frequency domain equalization is made localized. Conventional localized q-tap frequency domain equalizer still bears a formidable computational complexity of O(K2q), where K is the number of subcarriers. By further restricting the observation window size, sliding-window (SW) type of equalizer is proposed in the literature with complexity O(Kq3). This paper proposes a recursive SW LMMSE based equalizer which further reduces the computational complexity to O(Kq2) and more importantly without compromising performance.

On Reduced Complexity Decoding Algorithms for STBC-MTCM in Fast Fading Channels

STBC-MTCM scheme which achieves high rate, full diversity and large coding gains is an outstanding example of transmit diversity scheme for multiple-antenna system. In the case of time selective fast fading (TSFF) or frequency selective fading (FSF) channels, the performance of current existing STBC-MTCM decoder suffers from an irreducible error floor. In this paper, we present two computational efficient decoding algorithms: zero-forcing (ZF) detector and linear minimum mean square error (LMMSE) detector to combat the fast fading channels. The proposed decoding algorithms provide a robust performance across range of channel conditions from quasi-static (slow) fading to TSFF or FSF. Simulation results suggest that our proposed decoding algorithms have near maximum-likelihood (ML) performance while being computational more efficient

Antenna array geometry and coding performance

This paper provides details about experiments in realistic, urban, and frequency flat channels with space-time coding that specifically examines the impact of the number of receive antennas and the design criteria for code selection on the performance. Also the performance characteristics are examined of the coded modulations in the presence of finite size array geometries. This paper gives some insight into which of the theories are most useful in realistic deployments