Orthogonal frequency division multiplexing (OFDM) has been widely adopted in modern wireless communication systems due to its robustness against the frequency selectivity of wireless channels. For coherent detection, channel estimation is essential for receiver design. Channel estimation is also necessary for diversity combining or interference suppression where there are multiple receive antennas. In this paper, we will present a survey on channel estimation for OFDM. This survey will first review traditional channel estimation approaches based on channel frequency response (CFR). Parametric model (PM)-based channel estimation, which is particularly suitable for sparse channels, will be also investigated in this survey. Following the success of turbo codes and low-density parity check (LDPC) codes, iterative processing has been widely adopted in the design of receivers, and iterative channel estimation has received a lot of attention since that time. Iterative channel estimation will be emphasized in this survey as the emerging iterative receiver improves system performance significantly. The combination of multiple-input multiple-output (MIMO) and OFDM has been widely accepted in modern communication systems, and channel estimation in MIMO-OFDM systems will also be addressed in this survey. Open issues and future work are discussed at the end of this paper.

Channel Estimation for OFDM

Near-Capacity Multi-Functional MIMO Systems

About the Authors. OtherWiley IEEE Press Books on Related Topics. Preface. Acknowledgments. 1 Problem Formulation, Objectives and Benefits. 1.1 TheWireless Channel and the Concept of Diversity. 1.2 Diversity and Multiplexing Trade-offs in Multi-functional MIMO Systems. 1.3 Coherent versus Non-coherent Detection for STBCs Using Co-located and Cooperative Antenna Elements. 1.4 Historical Perspective and State-of-the-Art Contributions. 1.5 Iterative Detection Schemes and their Convergence Analysis. 1.6 Outline and Novel Aspects of the Monograph. Part I Coherent Versus Differential Turbo Detection of Sphere-packing-aided Single-user MIMO Systems. List of Symbols in Part I. 2 Space-Time Block Code Design using Sphere Packing. 2.1 Introduction. 2.2 Design Criteria for Space-Time Signals. 2.3 Design Criteria for Time-correlated Fading Channels. 2.4 Orthogonal Space-Time Code Design using SP. 2.5 STBC-SP Performance. 2.6 Chapter Conclusions. 2.7 Chapter Summary. 3 Turbo Detection of Channel-coded STBC-SP Schemes. 3.1 Introduction. 3.2 System Overview. 3.3 Iterative Demapping. 3.4 Binary EXIT Chart Analysis. 3.5 Performance of Turbo-detected Bit-based STBC-SP Schemes. 3.6 Chapter Conclusions. 3.7 Chapter Summary. 4 Turbo Detection of Channel-coded DSTBC-SP Schemes. 4.1 Introduction. 4.2 Differential STBC using SP Modulation. 4.3 Bit-based RSC-coded Turbo-detected DSTBC-SP Scheme. 4.4 Chapter Conclusions. 4.5 Chapter Summary. 5 Three-stage Turbo-detected STBC-SP Schemes. 5.1 Introduction. 5.2 System Overview. 5.3 EXIT Chart Analysis. 5.4 Maximum Achievable Bandwidth Efficiency. 5.5 Performance of Three-stageTurbo-detected STBC-SP Schemes. 5.6 Chapter Conclusions. 5.7 Chapter Summary. 6 Symbol-based Channel-coded STBC-SP Schemes. 6.1 Introduction. 6.2 System Overview. 6.3 Symbol-based Iterative Decoding. 6.4 Non-binary EXIT Chart Analysis. 6.5 Performance of Bit-based and Symbol-based LDPC-coded STBC-SP Schemes. 6.6 Chapter Conclusions. 6.7 Chapter Summary. Part II Coherent Versus Differential Turbo Detection of Single-user and Cooperative MIMOs. List of Symbols in Part II. 7 Linear Dispersion Codes: An EXIT Chart Perspective. 7.1 Introduction and Outline. 7.2 Linear Dispersion Codes. 7.3 Link Between STBCs and LDCs. 7.4 EXIT-chart-based Design of LDCs. 7.5 EXIT-chart-based Design of IR-PLDCs. 7.6 Conclusion. 8 Differential Space-Time Block Codes: A Universal Approach. 8.1 Introduction and Outline. 8.2 System Model. 8.3 DOSTBCs. 8.4 DLDCs. 8.5 RSC-coded Precoder-aided DOSTBCs. 8.6 IRCC-coded Precoder-aided DLDCs. 8.7 Conclusion. 9 Cooperative Space-Time Block Codes. 9.1 Introduction and Outline. 9.2 Twin-layer CLDCs. 9.3 IRCC-coded Precoder-aided CLDCs. 9.4 Conclusion. Part III Differential Turbo Detection of Multi-functional MIMO-aided Multi-user and Cooperative Systems. List of Symbols in Part III. 10 Differential Space-Time Spreading. 10.1 Introduction. 10.2 DPSK. 10.3 DSTS Designusing Two Transmit Antennas. 10.4 DSTS Design Using Four Transmit Antennas. 10.5 Chapter Conclusions. 10.6 Chapter Summary. 11 Iterative Detection of Channel-coded DSTS Schemes. 11.1 Introduction. 11.2 Iterative Detection of RSC-coded DSTS Schemes. 11.3 Iterative Detection of RSC-coded and Unity-rate Precoded Four-antenna-aided DSTS-SP System. 11.4 Chapter Conclusions. 11.5 Chapter Summary. 12 Adaptive DSTS-assisted Iteratively Detected SP Modulation. 12.1 Introduction. 12.2 System Overview. 12.3 Adaptive DSTS-assisted SP Modulation. 12.4 VSF-based Adaptive Rate DSTS. 12.5 Variable-code-rate Iteratively Detected DSTS-SP System. 12.6 Results and Discussion. 12.7 Chapter Conclusion and Summary. 13 Layered Steered Space-Time Codes. 13.1 Introduction. 13.2 LSSTCs. 13.3 Capacity of LSSTCs. 13.4 Iterative Detection and EXIT Chart Analysis. 13.5 Results and Discussion. 13.6 Chapter Conclusions. 13.7 Chapter Summary. 14 DL LSSTS-aided Generalized MC DS-CDMA. 14.1 Introduction. 14.2 LSSTS-aided Generalized MCDS-CDMA. 14.3 Increasing the Number of Users by Employing TD and FD Spreading. 14.4 Iterative Detection and EXIT Chart Analysis. 14.5 Results and Discussion. 14.6 Chapter Conclusions. 14.7 Chapter Summary. 15 Distributed Turbo Coding. 15.1 Introduction. 15.2 Background of Cooperative Communications. 15.3 DTC. 15.4 Results and Discussion. 15.5 Chapter Conclusions. 15.6 Chapter Summary. 16 Conclusions and Future Research. 16.1 Summary and Conclusions. 16.2 Future Research Ideas. 16.3 Closing Remarks. A Gray Mapping and AGM Schemes for SP Modulation of Size L =16. B EXIT Charts of Various Bit-based Turbo-detected STBC-SP Schemes. C EXIT Charts of Various Bit-based Turbo-detected DSTBC-SP Schemes. D LDCs' / for QPSK Modulation. E DLDCs' / for 2PAM Modulation. F CLDCs' / 1 and / 2 for BPSK Modulation. G Weighting Coefficient Vectors e and a. H Gray Mapping and AGM Schemes for SP Modulation of Size L =16. Glossary. Bibliography. Index. Author Index.

Near-Capacity Multi-Functional MIMO Systems: Sphere-Packing, Iterative Detection and Cooperation

Covering the full range of channel codes from the most conventional through to the most advanced, the second edition of Turbo Coding, Turbo Equalisation and Space-Time Coding is a self-contained reference on channel coding for wireless channels. The book commences with a historical perspective on the topic, which leads to two basic component codes, convolutional and block codes. It then moves on to turbo codes which exploit iterative decoding by using algorithms, such as the Maximum-A-Posteriori (MAP), Log-MAP and Soft Output Viterbi Algorithm (SOVA), comparing their performance. It also compares Trellis Coded Modulation (TCM), Turbo Trellis Coded Modulation (TTCM), Bit-Interleaved Coded Modulation (BICM) and Iterative BICM (BICM-ID) under various channel conditions.The horizon of the content is then extended to incorporate topics which have found their way into diverse standard systems. These include space-time block and trellis codes, as well as other Multiple-Input Multiple-Output (MIMO) schemes and near-instantaneously Adaptive Quadrature Amplitude Modulation (AQAM). The book also elaborates on turbo equalisation by providing a detailed portrayal of recent advances in partial response modulation schemes using diverse channel codes.A radically new aspect for this second edition is the discussion of multi-level coding and sphere-packing schemes, Extrinsic Information Transfer (EXIT) charts, as well as an introduction to the family of Generalized Low Density Parity Check codes.This new edition includes recent advances in near-capacity turbo-transceivers as well as new sections on multi-level coding schemes and of Generalized Low Density Parity Check codesComparatively studies diverse channel coded and turbo detected systems to give all-inclusive information for researchers, engineers and students Details EXIT-chart based irregular transceiver designs Uses rich performance comparisons as well as diverse near-capacity design examples

Turbo Coding, Turbo Equalisation and Space-Time Coding: EXIT-Chart-Aided Near-Capacity Designs for Wireless Channels

An electronic receiver comprises a nonlinear distortion modeling circuit and a nonlinear distortion compensation circuit. The nonlinear distortion modeling circuit is operable to determine a plurality of sets of nonlinear distortion model parameter values, where each of the sets of nonlinear distortion model parameter values representing nonlinear distortion experienced by signals received by the electronic receiver from a respective one a plurality of communication partners. The nonlinear distortion compensation circuit is operable to use the sets of nonlinear distortion model parameter values for processing of signals from the plurality of communication partners. Each of the sets of nonlinear distortion model parameter values may comprises a plurality of values corresponding to a plurality of signal powers. The sets of nonlinear distortion model parameters may be stored in a lookup table indexed by a signal strength parameter.

Communication methods and systems for nonlinear multi-user environments

We consider the design of iteratively decoded bit-interleaved space-time coded modulation (BI-STCM) over fast Rayleigh-fading channels with N/sub t/ transmit and N/sub r/ receive antennas. We propose the design criterion to achieve the largest asymptotic coding gain inherited in the constellation labeling. In particular, for orthogonal space-time block codes, the labeling design criterion reduces to maximizing the (-N/sub t/N/sub r/)th power mean of the complete set of squared Euclidean distances associated with all "error-free feedback" events in the constellation. Based on this power mean criterion, we show that the labeling optimization problem falls into the category of quadratic assignment problems for constellations of any shape and with an arbitrary number of transmit and receive antennas. For a set of practical values of N/sub t/ and N/sub r/, we present optimal labeling maps for 8-PSK, 16-QAM, and 64-QAM constellations.

Optimal constellation labeling for iteratively decoded bit-interleaved space-time coded Modulation

In embodiments, an adaptive tone erasure technique is applied to orthogonal frequency division multiplexing (OFDM) communications, such as ECMA-368 standard ultra-wideband (UWB) communications. A transmitter obtains jammed sub-carrier information and calculates an erasure mask. The jammed sub-carriers are nulled before transmitting to a receiver. In accordance with the erasure mask, bits falling on the jammed sub-carriers are replaced by erasure bits before interleaving, keeping the interleaver block size constant notwithstanding variations in the number of the jammed sub-carriers. The receiver also obtains the jammed sub-carrier information and the erasure mask. After the receiver deinterleaves the constant size blocks, it decodes the data without the erasure bits. The transmitter may detect the jammed sub-carriers itself, or obtain the information from the receiver. The receiver similarly may detect the jammed sub-carriers itself, or obtain the information from the transmitter.

Apparatus and method for interference-adaptive communications

We analyze the impact of imperfect channel state information (CSI) on the performance of bit-interleaved coded modulation with iterative decoding (BICM-ID) over fading channels. We develop a general, accurate and efficient theoretical error-free feedback bound (EF bound) to analyze the asymptotic bit-error rate (BER) of BICM-ID with imperfect CSI, and predict the BER floor due to channel estimation error. The convergence to the EF bound and the accuracy of the BER floor prediction are verified by simulation with various sets of code and channel parameters. These results are canonical, in that they apply to a variety of system configurations. Pilot symbol assisted modulation is used as a particular example for Rayleigh-fading channels.

16-QAM BICM-ID in fading channels with imperfect channel state information

Iteratively decoded bit-interleaved space-time coded modulation (BI-STCM) greatly lowers bit error rate (BER) over fast Rayleigh fading multiple-input multiple-output (MIMO) channels. We develop a general, tight and efficient theoretical error-free feedback bound (EF bound) to analyze the asymptotic BER. The convergence to the EF bound and the accuracy of the prediction are verified by simulation. With the best rate 1/2 4-state convolutional code and the 16-QAM modified set partitioning labeling, the BER of 10/sup -6/ can be achieved at E/sub b//N/sub 0/=1.6 dB with 2 transmit and 2 receive antennas.

Tight BER bounds for iteratively decoded bit-interleaved space-time coded modulation

We design constellation labeling maps for bit-interleaved space-time coded modulation with iterative decoding (BI-STCM-ID) over Rayleigh block-fading channels using the Alamouti scheme and N/sub r/ receive antennas. To achieve the largest asymptotic coding gain from the constellation labeling, we propose a new design criterion that maximizes the (-2N/sub r/)-th power mean of the squared Euclidean distances associated with all "error-free feedback" events in the constellation. Based on this power mean criterion, we show that the labeling optimization problem falls into the category of quadratic assignment problems. We propose two novel 16-QAM labeling maps that are particularly designed for N/sub r/=1 and N/sub r/=2, respectively. Numerical results show that both labeling maps achieve about 1 dB coding gain over the conventional 16-QAM modified set partitioning labeling.

Yuheng Huang

Papers

Optimal constellation labeling for iteratively decoded bit-interleaved space-time coded Modulation

Apparatus and method for interference-adaptive communications

16-QAM BICM-ID in fading channels with imperfect channel state information

Tight BER bounds for iteratively decoded bit-interleaved space-time coded modulation

Improved 16-QAM constellation labeling for BI-STCM-ID with the Alamouti scheme