600 research outputs found
Parallel Searching-Based Sphere Detector for MIMO Downlink OFDM Systems
In this paper, implementation of a detector with parallel partial candidate-search algorithm is described. Two fully independent partial candidate search processes are simultaneously employed for two groups of transmit antennas based
on QR decomposition (QRD) and QL decomposition (QLD) of a multiple-input multiple-output (MIMO) channel matrix. By using separate simultaneous candidate searching processes, the proposed implementation of QRD-QLD searching-based sphere detector provides a smaller latency and a lower computational complexity
than the original QRD-M detector for similar error-rate performance in wireless communications systems employing four transmit and four receive antennas with 16-QAM or 64-QAM constellation size. It is shown that in coded MIMO orthogonal
frequency division multiplexing (MIMO OFDM) systems, the detection latency and computational complexity of a receiver can be substantially reduced by using the proposed QRD-QLD detector implementation. The QRD-QLD-based sphere detector is also implemented using Field Programmable Gate Array (FPGA) and application specific integrated circuit (ASIC), and its hardware design complexity is compared with that of other sphere detectors reported in the literature.Nokia Renesas MobileTexas InstrumentsXilinxNational Science Foundatio
MIMO Transmission with Residual Transmit-RF Impairments
Physical transceiver implementations for multiple-input multiple-output
(MIMO) wireless communication systems suffer from transmit-RF (Tx-RF)
impairments. In this paper, we study the effect on channel capacity and
error-rate performance of residual Tx-RF impairments that defy proper
compensation. In particular, we demonstrate that such residual distortions
severely degrade the performance of (near-)optimum MIMO detection algorithms.
To mitigate this performance loss, we propose an efficient algorithm, which is
based on an i.i.d. Gaussian model for the distortion caused by these
impairments. In order to validate this model, we provide measurement results
based on a 4-stream Tx-RF chain implementation for MIMO orthogonal
frequency-division multiplexing (OFDM).Comment: to be presented at the International ITG Workshop on Smart Antennas -
WSA 201
Efficient DSP and Circuit Architectures for Massive MIMO: State-of-the-Art and Future Directions
Massive MIMO is a compelling wireless access concept that relies on the use
of an excess number of base-station antennas, relative to the number of active
terminals. This technology is a main component of 5G New Radio (NR) and
addresses all important requirements of future wireless standards: a great
capacity increase, the support of many simultaneous users, and improvement in
energy efficiency. Massive MIMO requires the simultaneous processing of signals
from many antenna chains, and computational operations on large matrices. The
complexity of the digital processing has been viewed as a fundamental obstacle
to the feasibility of Massive MIMO in the past. Recent advances on
system-algorithm-hardware co-design have led to extremely energy-efficient
implementations. These exploit opportunities in deeply-scaled silicon
technologies and perform partly distributed processing to cope with the
bottlenecks encountered in the interconnection of many signals. For example,
prototype ASIC implementations have demonstrated zero-forcing precoding in real
time at a 55 mW power consumption (20 MHz bandwidth, 128 antennas, multiplexing
of 8 terminals). Coarse and even error-prone digital processing in the antenna
paths permits a reduction of consumption with a factor of 2 to 5. This article
summarizes the fundamental technical contributions to efficient digital signal
processing for Massive MIMO. The opportunities and constraints on operating on
low-complexity RF and analog hardware chains are clarified. It illustrates how
terminals can benefit from improved energy efficiency. The status of technology
and real-life prototypes discussed. Open challenges and directions for future
research are suggested.Comment: submitted to IEEE transactions on signal processin
Parallel QR decomposition in LTE-A systems
The QR Decomposition (QRD) of communication channel matrices is a fundamental
prerequisite to several detection schemes in Multiple-Input Multiple-Output
(MIMO) communication systems. Herein, the main feature of the QRD is to
transform the non-causal system into a causal system, where consequently
efficient detection algorithms based on the Successive Interference
Cancellation (SIC) or Sphere Decoder (SD) become possible. Also, QRD can be
used as a light but efficient antenna selection scheme. In this paper, we
address the study of the QRD methods and compare their efficiency in terms of
computational complexity and error rate performance. Moreover, a particular
attention is paid to the parallelism of the QRD algorithms since it reduces the
latency of the matrix factorization.Comment: The eleventh IEEE International Workshop on Signal Processing
Advances for Wireless Communications, 5 pages, 4 figures, 4 algorithms, 1
tabl
Large-Scale MIMO Detection for 3GPP LTE: Algorithms and FPGA Implementations
Large-scale (or massive) multiple-input multiple-output (MIMO) is expected to
be one of the key technologies in next-generation multi-user cellular systems,
based on the upcoming 3GPP LTE Release 12 standard, for example. In this work,
we propose - to the best of our knowledge - the first VLSI design enabling
high-throughput data detection in single-carrier frequency-division multiple
access (SC-FDMA)-based large-scale MIMO systems. We propose a new approximate
matrix inversion algorithm relying on a Neumann series expansion, which
substantially reduces the complexity of linear data detection. We analyze the
associated error, and we compare its performance and complexity to those of an
exact linear detector. We present corresponding VLSI architectures, which
perform exact and approximate soft-output detection for large-scale MIMO
systems with various antenna/user configurations. Reference implementation
results for a Xilinx Virtex-7 XC7VX980T FPGA show that our designs are able to
achieve more than 600 Mb/s for a 128 antenna, 8 user 3GPP LTE-based large-scale
MIMO system. We finally provide a performance/complexity trade-off comparison
using the presented FPGA designs, which reveals that the detector circuit of
choice is determined by the ratio between BS antennas and users, as well as the
desired error-rate performance.Comment: To appear in the IEEE Journal of Selected Topics in Signal Processin
Improving Fixed-Point Implementation of QR Decomposition by Rounding-to-Nearest
QR decomposition is a key operation in many
current communication systems. This paper shows how to reduce
the area of a fixed-point QR decomposition implementation
based on Givens rotations by using a new number representation
system. This new representation allows performing round-tonearest
at the same cost of truncation. Consequently, the
rounding errors of the results are halved, which allows it to
reduce the word-length by one bit. This reduction positively
impacts on the area, delay and power consumption of the design.Ministry of Education and Science of Spain and Junta of AndalucĂa under contracts TIN2013-42253-P
and TIC-1692, respectively, and Universidad de Málaga. Campus de Excelencia Internacional AndalucĂa Tech
Hardware implementation of multiple-input multiple-output transceiver for wireless communication
This dissertation proposes an efficient hardware implementation scheme for iterative multi-input multi-output orthogonal frequency-division multiplexing (MIMO-OFDM) transceiver. The transmitter incorporates linear precoder designed with instantaneous channel state information (CSI). The receiver implements MMSE-IC (minimum mean square error interference cancelation) detector, channel estimator, low-density parity-check (LDPC) decoder and other supporting modules. The proposed implementation uses QR decomposition (QRD) of complex-valued matrices with four co-ordinate rotation digital computer (CORDIC) cores and back substitution to achieve the best tradeoff between resource and throughput. The MIMO system is used in field test and the results indicate that the instantaneous CSI varies very fast in practices and the performance of linear precoder designed with instantaneous CSI is limited. Instead, statistic CSI had to be used.
This dissertation also proposes a higher-rank principle Kronecker model (PKM). That exploits the statistic CSI to simulate the fading channels. The PKM is constructed by decomposing the channel correlation matrices with the higher-order singular value decomposition (HOSVD) method. The proposed PKM-HOSVD model is validated by extensive field experiments conducted for 4-by-4 MIMO systems in both indoor and outdoor environments. The results confirm that the statistic CSI varies slowly and the PKM-HOSVD will be helpful in the design of linear precoders. --Abstract, page iv
Polynomial matrix decomposition techniques for frequency selective MIMO channels
For a narrowband, instantaneous mixing multi-input, multi-output (MIMO) communications system,
the channel is represented as a scalar matrix. In this scenario, singular value decomposition (SVD)
provides a number of independent spatial subchannels which can be used to enhance data rates or to increase diversity. Alternatively, a QR decomposition can be used to reduce the MIMO channel equalization problem to a set of single channel equalization problems.
In the case of a frequency selective MIMO system, the multipath channel is represented as a polynomial matrix. Thus conventional matrix decomposition techniques can no longer be applied. The traditional solution to this broadband problem is to reduce it to narrowband form by using a discrete Fourier transform (DFT) to split the broadband channel into N narrow uniformly spaced frequency bands and applying scalar decomposition techniques within each band. This describes an orthogonal frequency division multiplexing (OFDM) based system.
However, a novel algorithm has been developed for calculating the eigenvalue decomposition of a
para-Hermitian polynomial matrix, known as the sequential best rotation (SBR2) algorithm. SBR2
and its QR based derivatives allow a true polynomial singular value and QR decomposition to be
formulated. The application of these algorithms within frequency selective MIMO systems results in
a fundamentally new approach to exploiting spatial diversity.
Polynomial matrix decomposition and OFDM based solutions are compared for a wide variety of
broadband MIMO communication systems. SVD is used to create a robust, high gain communications
channel for ultra low
signal-to-noise ratio (SNR) environments. Due to the frequency selective nature
of the channels produced by polynomial matrix decomposition, additional processing is required at the receiver resulting in two distinct equalization techniques based around turbo and Viterbi equalization. The proposed approach is found to provide identical performance to that of an existing OFDM scheme while supporting a wider range of access schemes. This work is then extended to QR decomposition
based communications systems, where the proposed polynomial approach is found to not only provide superior bit-error-rate (BER) performance but significantly reduce the complexity of transmitter
design. Finally both techniques are combined to create a nulti-user MIMO system that provides superior BER performance over an OFDM based scheme. Throughout the work the robustness of the proposed scheme to channel state information (CSI) error is considered, resulting in a rigorous
demonstration of the capabilities of the polynomial approach
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