1,118 research outputs found
A Novel Data-Aided Channel Estimation with Reduced Complexity for TDS-OFDM Systems
In contrast to the classical cyclic prefix (CP)-OFDM, the time domain
synchronous (TDS)-OFDM employs a known pseudo noise (PN) sequence as guard
interval (GI). Conventional channel estimation methods for TDS-OFDM are based
on the exploitation of the PN sequence and consequently suffer from intersymbol
interference (ISI). This paper proposes a novel dataaided channel estimation
method which combines the channel estimates obtained from the PN sequence and,
most importantly, additional channel estimates extracted from OFDM data
symbols. Data-aided channel estimation is carried out using the rebuilt OFDM
data symbols as virtual training sequences. In contrast to the classical turbo
channel estimation, interleaving and decoding functions are not included in the
feedback loop when rebuilding OFDM data symbols thereby reducing the
complexity. Several improved techniques are proposed to refine the data-aided
channel estimates, namely one-dimensional (1-D)/two-dimensional (2-D) moving
average and Wiener filtering. Finally, the MMSE criteria is used to obtain the
best combination results and an iterative process is proposed to progressively
refine the estimation. Both MSE and BER simulations using specifications of the
DTMB system are carried out to prove the effectiveness of the proposed
algorithm even in very harsh channel conditions such as in the single frequency
network (SFN) case
Enhanced Two-Dimensional Data-aided Channel Estimation for TDS-OFDM
International audienceIn time domain synchronous (TDS)-OFDM, the channel estimation is conventionally carried out based on the pseudo noise (PN) sequence. The PN sequence based channel estimation however suffers interference from adjacent OFDM data symbols. This paper proposes a new low-complexity dataaided channel estimation method with two-dimensional (2-D) estimate refinement and interpolation. Data-aided channel estimation is carried out using the rebuilt OFDM data symbols as virtual training symbols. In contrast to the classical turbo channel estimation, interleaving and decoding functions are not used when rebuilding OFDM data symbols thereby reducing the complexity. 2-D estimate refinement and interpolation are proposed to improve the data-aided channel estimation. Simulation results show that the performance of TDS-OFDM based DTMB system using the proposed method is very close to that with perfect channel estimation in terms of bit error rate (BER)
Estimation of phase noise in oscillators with colored noise sources
In this letter we study the design of algorithms for estimation of phase
noise (PN) with colored noise sources. A soft-input maximum a posteriori PN
estimator and a modified soft-input extended Kalman smoother are proposed. The
performance of the proposed algorithms are compared against those studied in
the literature, in terms of mean square error of PN estimation, and symbol
error rate of the considered communication system. The comparisons show that
considerable performance gains can be achieved by designing estimators that
employ correct knowledge of the PN statistics
Feedforward data-aided phase noise estimation from a DCT basis expansion
This contribution deals with phase noise estimation from pilot symbols. The phase noise process is approximated by an expansion of discrete cosine transform (DCT) basis functions containing only a few terms. We propose a feedforward algorithm that estimates the DCT coefficients without requiring detailed knowledge about the phase noise statistics. We demonstrate that the resulting (linearized) mean-square phase estimation error consists of two contributions: a contribution from the additive noise, that equals the Cramer-Rao lower bound, and a noise independent contribution, that results front the phase noise modeling error. We investigate the effect of the symbol sequence length, the pilot symbol positions, the number of pilot symbols, and the number of estimated DCT coefficients it the estimation accuracy and on the corresponding bit error rate (PER). We propose a pilot symbol configuration allowing to estimate any number of DCT coefficients not exceeding the number of pilot Symbols, providing a considerable Performance improvement as compared to other pilot symbol configurations. For large block sizes, the DCT-based estimation algorithm substantially outperforms algorithms that estimate only the time-average or the linear trend of the carrier phase. Copyright (C) 2009 J. Bhatti and M. Moeneclaey
Cloud Transmission: System Performance and Application Scenarios
[EN] Cloud Transmission (Cloud Txn) System is a
flexible multi-layer system that uses spectrum overlay technology
to simultaneously deliver multiple program streams with
different characteristics and robustness for different services
(mobile TV, HDTV and UHDTV) in one RF channel. The
transmitted signal is formed by superimposing a number of
independent signals at desired power levels, to form a multilayered
signal. The signals of different layers can have different
coding, bit rate, and robustness. For the top layer, system
parameters are chosen to provide very robust transmission that
can be used for high speed mobile broadcasting service to
portable devices. The bit rate is traded for more powerful error
correction coding and robustness so that the Signal to Noise
Ratio (SNR) threshold at the receiver is a negative value in the
range of -2 to -3 dB. The top layer is designed to withstand
combined noise, co-channel interference and multipath distortion
power levels higher than the desired signal power. The lowerlayer
signal can be DVB-T2 signal or other newly designed
system to deliver HDTV/UHDTV to fixed receivers. The system
concept is open to technological advances that might come in the
future: all new technologies, BICM/Non Uuniform-QAM, rotated
constellations, Time Frequency Slicing or MIMO techniques can
be implemented in the Cloud Txn lower (high data) rate layer.
The main focus of this paper is to thoroughly describe the
performance of this newly presented Cloud Transmission
broadcasting system.This work has been financially supported in part by the University of the
Basque Country UPV/EHU (UFI 11/30), by the Basque Government (IT-683-
13 and SAIOTEK), by the Spanish Ministry of Science and Innovation under
the project NG-RADIATE (TEC2009-14201), and by the Spanish Ministry of
Economy and Competitiveness under the project HEDYT-GBB (TEC2012-
33302
Orthogonal STBC MC-CDMA system with channel estimation over realistic high mobility MIMO channels
Non
Advanced Channel Estimation Techniques for Multiple-Input Multiple-Output Multi-Carrier Systems in Doubly-Dispersive Channels
Flexible numerology of the physical layer has been introduced in the latest release of 5G new radio (NR) and the baseline waveform generation is chosen to be cyclic-prefix based orthogonal frequency division multiplexing (CP-OFDM). Thanks to the narrow subcarrier spacing and low complexity one tap equalization (EQ) of OFDM, it suits well to time-dispersive channels. For the upcoming 5G and beyond use-case scenarios, it is foreseen that the users might experience high mobility conditions. While the frame structure of the 5G NR is designed for long coherence times, the synchronization and channel estimation (CE) procedures are not fully and reliably covered for diverse applications.
The research on alternative multi-carrier waveforms has brought up valuable results in terms of spectral efficiency, applications coexistence and flexibility. Nevertheless, the receiver design becomes more challenging for multiple-input multiple-output (MIMO) non-orthogonal multi-carriers because the receiver must deal with multiple dimensions of interference. This thesis aims to deliver accurate pilot-aided estimations of the wireless channel for coherent detection. Considering a MIMO non-orthogonal multi-carrier, e.g. generalized frequency division multiplexing (GFDM), we initially derive the classical and Bayesian estimators for rich multi-path fading channels, where we theoretically assess the choice of pilot design. Moreover, the well time- and frequency-localization of the pilots in non-orthogonal multi-carriers allows to reuse their energy from cyclic-prefix (CP). Taking advantage of this feature, we derive an iterative approach for joint CE and EQ of MIMO systems. Furthermore, exploiting the block-circularity of GFDM, we comprehensively analyze the complexity aspects, and propose a solution for low complexity implementation.
Assuming very high mobility use-cases where the channel varies within the symbol duration, further considerations, particularly the channel coherence time must be taken into account. A promising candidate that is fully independent of the multi-carrier choice is unique word (UW) transmission, where the CP of random nature is replaced by a deterministic sequence. This feature, allows per-block synchronization and channel estimation for robust transmission over extremely doubly-dispersive channels. In this thesis, we propose a novel approach to extend the UW-based physical layer design to MIMO systems and we provide an in-depth study of their out-of-band emission, synchronization, CE and EQ procedures. Via theoretical derivations and simulation results, and comparisons with respect to the state-of-the-art CP-OFDM systems, we show that the proposed UW-based frame design facilitates robust transmission over extremely doubly-dispersive channels.:1 Introduction 1
1.1 Multi-Carrier Waveforms 1
1.2 MIMO Systems 3
1.3 Contributions and Thesis Structure 4
1.4 Notations 6
2 State-of-the-art and Fundamentals 9
2.1 Linear Systems and Problem Statement 9
2.2 GFDM Modulation 11
2.3 MIMO Wireless Channel 12
2.4 Classical and Bayesian Channel Estimation in MIMO OFDM Systems 15
2.5 UW-Based Transmission in SISO Systems 17
2.6 Summary 19
3 Channel Estimation for MIMO Non-Orthogonal Waveforms 21
3.1 Classical and Bayesian Channel Estimation in MIMO GFDM Systems 22
3.1.1 MIMO LS Channel Estimation 23
3.1.2 MIMO LMMSE Channel Estimation 24
3.1.3 Simulation Results 25
3.2 Basic Pilot Designs for GFDM Channel Estimation 29
3.2.1 LS/HM Channel Estimation 31
3.2.2 LMMSE Channel Estimation for GFDM 32
3.2.3 Error Characterization 33
3.2.4 Simulation Results 36
3.3 Interference-Free Pilot Insertion for MIMO GFDM Channel Estimation 39
3.3.1 Interference-Free Pilot Insertion 39
3.3.2 Pilot Observation 40
3.3.3 Complexity 41
3.3.4 Simulation Results 41
3.4 Bayesian Pilot- and CP-aided Channel Estimation in MIMO NonOrthogonal Multi-Carriers 45
3.4.1 Review on System Model 46
3.4.2 Single-Input-Single-Output Systems 47
3.4.3 Extension to MIMO 50
3.4.4 Application to GFDM 51
3.4.5 Joint Channel Estimation and Equalization via LMMSE Parallel Interference Cancellation 57
3.4.6 Complexity Analysis 61
3.4.7 Simulation Results 61
3.5 Pilot- and CP-aided Channel Estimation in Time-Varying Scenarios 67
3.5.1 Adaptive Filtering based on Wiener-Hopf Approac 68
3.5.2 Simulation Results 69
3.6 Summary 72
4 Design of UW-Based Transmission for MIMO Multi-Carriers 73
4.1 Frame Design, Efficiency and Overhead Analysis 74
4.1.1 Illustrative Scenario 74
4.1.2 CP vs. UW Efficiency Analysis 76
4.1.3 Numerical Results 77
4.2 Sequences for UW and OOB Radiation 78
4.2.1 Orthogonal Polyphase Sequences 79
4.2.2 Waveform Engineering for UW Sequences combined with GFDM 79
4.2.3 Simulation Results for OOB Emission of UW-GFDM 81
4.3 Synchronization 82
4.3.1 Transmission over a Centralized MIMO Wireless Channel 82
4.3.2 Coarse Time Acquisition 83
4.3.3 CFO Estimation and Removal 85
4.3.4 Fine Time Acquisition 86
4.3.5 Simulation Results 88
4.4 Channel Estimation 92
4.4.1 MIMO UW-based LMMSE CE 92
4.4.2 Adaptive Filtering 93
4.4.3 Circular UW Transmission 94
4.4.4 Simulation Results 95
4.5 Equalization with Imperfect Channel Knowledge 96
4.5.1 UW-Free Equalization 97
4.5.2 Simulation Results 99
4.6 Summary 102
5 Conclusions and Perspectives 103
5.1 Main Outcomes in Short 103
5.2 Open Challenges 105
A Complementary Materials 107
A.1 Linear Algebra Identities 107
A.2 Proof of lower triangular Toeplitz channel matrix being defective 108
A.3 Calculation of noise-plus-interference covariance matrix for Pilot- and CPaided CE 108
A.4 Bock diagonalization of the effective channel for GFDM 109
A.5 Detailed complexity analysis of Sec. 3.4 109
A.6 CRLB derivations for the pdf (4.24) 113
A.7 Proof that (4.45) emulates a circular CIR at the receiver 11
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