1,128 research outputs found
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
Ubiquitous Cell-Free Massive MIMO Communications
Since the first cellular networks were trialled in the 1970s, we have
witnessed an incredible wireless revolution. From 1G to 4G, the massive traffic
growth has been managed by a combination of wider bandwidths, refined radio
interfaces, and network densification, namely increasing the number of antennas
per site. Due its cost-efficiency, the latter has contributed the most. Massive
MIMO (multiple-input multiple-output) is a key 5G technology that uses massive
antenna arrays to provide a very high beamforming gain and spatially
multiplexing of users, and hence, increases the spectral and energy efficiency.
It constitutes a centralized solution to densify a network, and its performance
is limited by the inter-cell interference inherent in its cell-centric design.
Conversely, ubiquitous cell-free Massive MIMO refers to a distributed Massive
MIMO system implementing coherent user-centric transmission to overcome the
inter-cell interference limitation in cellular networks and provide additional
macro-diversity. These features, combined with the system scalability inherent
in the Massive MIMO design, distinguishes ubiquitous cell-free Massive MIMO
from prior coordinated distributed wireless systems. In this article, we
investigate the enormous potential of this promising technology while
addressing practical deployment issues to deal with the increased
back/front-hauling overhead deriving from the signal co-processing.Comment: Published in EURASIP Journal on Wireless Communications and
Networking on August 5, 201
Channel Estimation for MIMO MC-CDMA Systems
The concepts of MIMO MC-CDMA are not new but the new technologies to improve
their functioning are an emerging area of research. In general, most mobile
communication systems transmit bits of information in the radio space to the
receiver. The radio channels in mobile radio systems are usually multipath
fading channels, which cause inter-symbol interference (ISI) in the received
signal. To remove ISI from the signal, there is a need of strong equalizer. In
this thesis we have focused on simulating the MIMO MC-CDMA systems in MATLAB
and designed the channel estimation for them
Massive MIMO is a Reality -- What is Next? Five Promising Research Directions for Antenna Arrays
Massive MIMO (multiple-input multiple-output) is no longer a "wild" or
"promising" concept for future cellular networks - in 2018 it became a reality.
Base stations (BSs) with 64 fully digital transceiver chains were commercially
deployed in several countries, the key ingredients of Massive MIMO have made it
into the 5G standard, the signal processing methods required to achieve
unprecedented spectral efficiency have been developed, and the limitation due
to pilot contamination has been resolved. Even the development of fully digital
Massive MIMO arrays for mmWave frequencies - once viewed prohibitively
complicated and costly - is well underway. In a few years, Massive MIMO with
fully digital transceivers will be a mainstream feature at both sub-6 GHz and
mmWave frequencies. In this paper, we explain how the first chapter of the
Massive MIMO research saga has come to an end, while the story has just begun.
The coming wide-scale deployment of BSs with massive antenna arrays opens the
door to a brand new world where spatial processing capabilities are
omnipresent. In addition to mobile broadband services, the antennas can be used
for other communication applications, such as low-power machine-type or
ultra-reliable communications, as well as non-communication applications such
as radar, sensing and positioning. We outline five new Massive MIMO related
research directions: Extremely large aperture arrays, Holographic Massive MIMO,
Six-dimensional positioning, Large-scale MIMO radar, and Intelligent Massive
MIMO.Comment: 20 pages, 9 figures, submitted to Digital Signal Processin
Classical and Bayesian Linear Data Estimators for Unique Word OFDM
Unique word - orthogonal frequency division multiplexing (UW-OFDM) is a novel
OFDM signaling concept, where the guard interval is built of a deterministic
sequence - the so-called unique word - instead of the conventional random
cyclic prefix. In contrast to previous attempts with deterministic sequences in
the guard interval the addressed UW-OFDM signaling approach introduces
correlations between the subcarrier symbols, which can be exploited by the
receiver in order to improve the bit error ratio performance. In this paper we
develop several linear data estimators specifically designed for UW-OFDM, some
based on classical and some based on Bayesian estimation theory. Furthermore,
we derive complexity optimized versions of these estimators, and we study their
individual complex multiplication count in detail. Finally, we evaluate the
estimators' performance for the additive white Gaussian noise channel as well
as for selected indoor multipath channel scenarios.Comment: Preprint, 13 page
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