I-Wei Lai

Baseband Receiver Design for Wireless MIMO-OFDM Communications: Chiueh/Baseband Receiver Design for Wireless MIMO-OFDM Communications

The Second Edition of OFDM Baseband Receiver Design for Wirless Communications, this book expands on the earlier edition with enhanced coverage of MIMO techniques, additional baseband algorithms, and more IC design examples. The authors cover the full range of OFDM technology, from theories and algorithms to architectures and circuits.The book gives a concise yet comprehensive look at digital communication fundamentals before explaining signal processing algorithms in receivers. The authors give detailed treatment of hardware issues - from architecture to IC implementation.Links OFDM and MIMO theory with hardware implementationEnables the reader to transfer communication received concepts into hardware; design wireless receivers with acceptable implemntation loss; achieve low-power designsCovers the latest standards, such as DVB-T2, WiMax, LTE and LTE-AIncludes more baseband algorithms, like soft-decoding algorithms such as BCJR and SOVAExpanded treatment of channel models, detection algorithms and MIMO techniquesFeatures concrete design examples of WiMAX systems and cognitive radio apllications Companion website with lecture slides for instructorsBased on materials developed for a course in digital communication IC design, this book is ideal for graduate students and researchers in VLSI design, wireless communications, and communications signal processing. Practicing engineers working on algorithms or hardware for wireless communications devices will also find this to be a key reference.

Combining orthogonalized partial metrics: Efficient enumeration for soft-input sphere decoder

Using the Schnorr-Euchner (SE) order for soft-input sphere decoders is inefficient for implementation, because it requires exhaustive calculation and sorting of partial metrics of all constellation points. Instead, low-complexity methods can be applied by separating the partial metric into channel information and a priori information and solely enumerating based on one of them. With such an orthogonalization, this paper presents an algorithm that effectively combines these two enumerations to deliver an order close to the SE one. Mathematical analyses and simulation results demonstrate that this is the first algorithm allowing for a low-complexity implementation with optimal error rate performance for any number of iterations.

Efficient Channel-Adaptive MIMO Detection Using Just-Acceptable Error Rate

This paper proposes a new concept of multiple-input multiple-output (MIMO) detection, aiming at minimizing the average computational cost. The detection methods are adapted according to the estimated channel state information to deliver just-acceptable error rate (JAER) performance. Error rate models for two popular MIMO detection algorithms are derived given the channel matrix. From these models, a channel-adaptive-MIMO (CA-MIMO) receiver with detector-switching strategies is proposed. Simulation results demonstrate that the proposed CA-MIMO detector meets the JAER criterion efficiently. Compared with the sophisticated Sphere Search (SS) MIMO detector, the average saving at moderate signal-to-noise ratio (SNR) is around 58% to 72%, depending on different modulation alphabets. At high SNR, the CA-MIMO detector almost always switch to Zero-Forcing (ZF) detection, where the complexity is several orders lower than the SS detector.

Complexity-efficient enumeration techniques for soft-input, soft-output sphere decoding

In this paper two complexity efficient soft sphere-decoder modifications are proposed for computing the max-log LLR values in iterative MIMO systems, which avoid the costly, typically needed, full enumeration and sorting (FES) procedure during the tree traversal without compromising the max-log performance. It is shown that despite the resulting increase in the number of expanded nodes, they can be more computationally efficient than the typical soft sphere decoders by avoiding the unnecessary complexity of FES.

One-dimensional interpolation based channel estimation for mobile DVB-H reception

Orthogonal frequency-division multiplexing (OFDM) modulation provides a high data rate communication service. However, in mobile reception, a loss of sub-carrier orthogonality due to Doppler-spread leads to inter-carrier interference (ICI). This paper proposes a channel estimation scheme based on one-dimensional raised cosine interpolation. A time-domain raised cosine interpolation plus a frequency-domain raise cosine interpolator with adaptive roll-off factor can estimate the channel response very well in high-mobility environments

Efficient Sequential Integer CFO and Sector Identity Detection for LTE Cell Search

In this letter, we propose an efficient algorithm for the detection of the integer carrier frequency offset (CFO) and sector identity used in the LTE cell search. For the conventional LTE cell search, the integer CFO and sector identity are jointly detected by utilizing the primary synchronization signal (PSS). By exploiting the symmetric property of the PSS, the integer CFO can be solely detected without the knowledge of sector identity, and thus, the joint detection of the integer CFO and sector identity is decoupled. Additionally, the proposed sequential integer CFO and sector identity detection (SISID) removes the effect of the channel frequency responses such that the detection accuracy is enhanced. We also design the SISID hardware architecture where the parts of the signals are processed in the polar coordinate so that all the multiplications are realized by additions/subtractions. The simulation results demonstrate that the proposed SISID achieves better detection accuracy than the conventional methods with only one third of the computational complexity.

Tight Approximation of the Bit Error Rate for BICM(-ID) Assuming Imperfect CSI

In this correspondence, we analytically derive the bit error rate (BER) for bit-interleaved coded modulation (BICM) under the assumption of a temporally correlated flat Rayleigh fading channel. We assume the channel state information (CSI) to be unknown at receiver side and consider a linear minimum mean-squared error (LMMSE) channel estimator that relies on periodically inserted pilot symbols. We give asymptotic results for both non-iterative BICM and BICM with iterative decoding (BICM-ID). Furthermore, we show that the interpretation of the channel estimation error as an SNR degradation holds true in these cases.

Low-complexity adaptive channel estimation for OFDM system in fast-fading channel

This paper presents a low-complexity interpolation-based channel estimator suited for scattered-pilot OFDM systems in fast-fading channel. The proposed estimator consists of two interpolators: one RLS interpolator for estimating scattered subcarriers along the time direction and another raised-cosine (RC) interpolator for estimating data subcarriers along the frequency direction. A low-complexity architecture tailored for DVB-T/H is demonstrated as an exemplar. Simulation results show that the proposed channel estimator has comparable accuracy with almost order-of-magnitude lower complexity than conventional adaptive channel estimators.

Asymptotic BER Analysis for MIMO-BICM with Zero-Forcing Detectors Assuming Imperfect CSI

In this paper, we derive the asymptotic bit error rate (BER) for multiple-input multiple-output bit-interleaved coded modulation (MIMO-BICM) with linear zero-forcing (ZF) receivers for a temporally correlated flat Rayleigh fading channel. Pilot symbol assisted modulation (PSAM) in combination with linear minimum mean-squared error (LMMSE) channel estimation is considered. We also demonstrate that the deterioration due to imperfect channel state information (CSI) can be represented by a signal-to-noise ratio (SNR) degradation.

Iterative channel estimation control for MIMO-OFDM Systems

Iterative channel estimation and decoding result in significant performance gains but at high computational cost. In this paper, an iterative channel estimation control is proposed to reduce the complexity by only refining the channel estimates which significantly affect the decoding performance. Simulation results demonstrate that significant complexity savings can be achieved with negligible error rate performance loss.