75 research outputs found
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
Iterative Joint Channel Estimation and Multi-User Detection for Multiple-Antenna Aided OFDM Systems
Multiple-Input-Multiple-Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) systems have recently attracted substantial research interest. However, compared to Single-Input-Single-Output (SISO) systems, channel estimation in the MIMO scenario becomes more challenging, owing to the increased number of independent transmitter-receiver links to be estimated. In the context of the Bell LAyered Space-Time architecture (BLAST) or Space Division Multiple Access (SDMA) multi-user MIMO OFDM systems, none of the known channel estimation techniques allows the number of users to be higher than the number of receiver antennas, which is often referred to as a “rank-deficient” scenario, owing to the constraint imposed by the rank of the MIMO channel matrix. Against this background, in this paper we propose a new Genetic Algorithm (GA) assisted iterative Joint Channel Estimation and Multi-User Detection (GA-JCEMUD) approach for multi-user MIMO SDMA-OFDM systems, which provides an effective solution to the multi-user MIMO channel estimation problem in the above-mentioned rank-deficient scenario. Furthermore, the GAs invoked in the data detection literature can only provide a hard-decision output for the Forward Error Correction (FEC) or channel decoder, which inevitably limits the system’s achievable performance. By contrast, our proposed GA is capable of providing “soft” outputs and hence it becomes capable of achieving an improved performance with the aid of FEC decoders. A range of simulation results are provided to demonstrate the superiority of the proposed scheme. Index Terms—Channel estimation, genetic algorithm, multiple-input-multiple-output, multi-user detection, orthogonal frequency division multiplexing, space division multiple access
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
Adaptive and Iterative Multi-Branch MMSE Decision Feedback Detection Algorithms for MIMO Systems
In this work, decision feedback (DF) detection algorithms based on multiple
processing branches for multi-input multi-output (MIMO) spatial multiplexing
systems are proposed. The proposed detector employs multiple cancellation
branches with receive filters that are obtained from a common matrix inverse
and achieves a performance close to the maximum likelihood detector (MLD).
Constrained minimum mean-squared error (MMSE) receive filters designed with
constraints on the shape and magnitude of the feedback filters for the
multi-branch MMSE DF (MB-MMSE-DF) receivers are presented. An adaptive
implementation of the proposed MB-MMSE-DF detector is developed along with a
recursive least squares-type algorithm for estimating the parameters of the
receive filters when the channel is time-varying. A soft-output version of the
MB-MMSE-DF detector is also proposed as a component of an iterative detection
and decoding receiver structure. A computational complexity analysis shows that
the MB-MMSE-DF detector does not require a significant additional complexity
over the conventional MMSE-DF detector, whereas a diversity analysis discusses
the diversity order achieved by the MB-MMSE-DF detector. Simulation results
show that the MB-MMSE-DF detector achieves a performance superior to existing
suboptimal detectors and close to the MLD, while requiring significantly lower
complexity.Comment: 10 figures, 3 tables; IEEE Transactions on Wireless Communications,
201
QRD-Assisted Adaptive Modulation-Aided MIMO Systems
Abstract—In this paper, we propose QR-decomposition (QRD)-based adaptive modulation (AM)-aided multiple-input–multiple-output (MIMO) systems. The proposed algorithm yields a tight lower bound of the free distance (FD), which determines the error probability of the detector in thehigh-signal-to-noise-ratio (SNR) region. Thus, this QRD-based AM algorithm is capable of achieving near-optimal performance at low complexity because the full QRD, which imposes high complexity, is performed only once for each channel realization, regardless of the number of AM modes.Our simulation results show that the proposed algorithm exhibits a better bit-error-rate (BER) performance and reduced complexity compared with the existing algorithms
QRD-QLD searching based sphere detection for emerging MIMO downlink OFDM receivers
In this paper, a detection algorithm with parallel partial candidate-search algorithm is presented. Two fully independent partial search processes are simultaneously employed for two groups of transmit antennas based on QR
and QL decompositions of the channel matrix. Proposed QRDQLD detection algorithm is compared with well-known QRD-M scheme adopted for several emerging wireless standards. Latency of the QRD-QLD candidate search is about twice as small
for similar error-rate performance and for identical hardware resources. Total detection latency of QRD-QLD algorithm that also includes computation of soft information for outer decoder is also substantially smaller.Nokia CorporationNational Science Foundatio
Multiuser MIMO-OFDM for Next-Generation Wireless Systems
This overview portrays the 40-year evolution of orthogonal frequency division multiplexing (OFDM) research. The amelioration of powerful multicarrier OFDM arrangements with multiple-input multiple-output (MIMO) systems has numerous benefits, which are detailed in this treatise. We continue by highlighting the limitations of conventional detection and channel estimation techniques designed for multiuser MIMO OFDM systems in the so-called rank-deficient scenarios, where the number of users supported or the number of transmit antennas employed exceeds the number of receiver antennas. This is often encountered in practice, unless we limit the number of users granted access in the base station’s or radio port’s coverage area. Following a historical perspective on the associated design problems and their state-of-the-art solutions, the second half of this treatise details a range of classic multiuser detectors (MUDs) designed for MIMO-OFDM systems and characterizes their achievable performance. A further section aims for identifying novel cutting-edge genetic algorithm (GA)-aided detector solutions, which have found numerous applications in wireless communications in recent years. In an effort to stimulate the cross pollination of ideas across the machine learning, optimization, signal processing, and wireless communications research communities, we will review the broadly applicable principles of various GA-assisted optimization techniques, which were recently proposed also for employment inmultiuser MIMO OFDM. In order to stimulate new research, we demonstrate that the family of GA-aided MUDs is capable of achieving a near-optimum performance at the cost of a significantly lower computational complexity than that imposed by their optimum maximum-likelihood (ML) MUD aided counterparts. The paper is concluded by outlining a range of future research options that may find their way into next-generation wireless systems
From Linear Equalization to Lattice-Reduction-Aided Sphere-Detector as an Answer to the MIMO Detection Problematic in Spatial Multiplexing Systems
ISBN 978-953-307-223-4International audienc
Adaptive Baseband Pro cessing and Configurable Hardware for Wireless Communication
The world of information is literally at one’s fingertips, allowing access to previously unimaginable amounts of data, thanks to advances in wireless communication. The growing demand for high speed data has necessitated theuse of wider bandwidths, and wireless technologies such as Multiple-InputMultiple-Output (MIMO) have been adopted to increase spectral efficiency.These advanced communication technologies require sophisticated signal processing, often leading to higher power consumption and reduced battery life.Therefore, increasing energy efficiency of baseband hardware for MIMO signal processing has become extremely vital. High Quality of Service (QoS)requirements invariably lead to a larger number of computations and a higherpower dissipation. However, recognizing the dynamic nature of the wirelesscommunication medium in which only some channel scenarios require complexsignal processing, and that not all situations call for high data rates, allowsthe use of an adaptive channel aware signal processing strategy to provide adesired QoS. Information such as interference conditions, coherence bandwidthand Signal to Noise Ratio (SNR) can be used to reduce algorithmic computations in favorable channels. Hardware circuits which run these algorithmsneed flexibility and easy reconfigurability to switch between multiple designsfor different parameters. These parameters can be used to tune the operations of different components in a receiver based on feedback from the digitalbaseband. This dissertation focuses on the optimization of digital basebandcircuitry of receivers which use feedback to trade power and performance. Aco-optimization approach, where designs are optimized starting from the algorithmic stage through the hardware architectural stage to the final circuitimplementation is adopted to realize energy efficient digital baseband hardwarefor mobile 4G devices. These concepts are also extended to the next generation5G systems where the energy efficiency of the base station is improved.This work includes six papers that examine digital circuits in MIMO wireless receivers. Several key blocks in these receiver include analog circuits thathave residual non-linearities, leading to signal intermodulation and distortion.Paper-I introduces a digital technique to detect such non-linearities and calibrate analog circuits to improve signal quality. The concept of a digital nonlinearity tuning system developed in Paper-I is implemented and demonstratedin hardware. The performance of this implementation is tested with an analogchannel select filter, and results are presented in Paper-II. MIMO systems suchas the ones used in 4G, may employ QR Decomposition (QRD) processors tosimplify the implementation of tree search based signal detectors. However,the small form factor of the mobile device increases spatial correlation, whichis detrimental to signal multiplexing. Consequently, a QRD processor capableof handling high spatial correlation is presented in Paper-III. The algorithm and hardware implementation are optimized for carrier aggregation, which increases requirements on signal processing throughput, leading to higher powerdissipation. Paper-IV presents a method to perform channel-aware processingwith a simple interpolation strategy to adaptively reduce QRD computationcount. Channel properties such as coherence bandwidth and SNR are used toreduce multiplications by 40% to 80%. These concepts are extended to usetime domain correlation properties, and a full QRD processor for 4G systemsfabricated in 28 nm FD-SOI technology is presented in Paper-V. The designis implemented with a configurable architecture and measurements show thatcircuit tuning results in a highly energy efficient processor, requiring 0.2 nJ to1.3 nJ for each QRD. Finally, these adaptive channel-aware signal processingconcepts are examined in the scope of the next generation of communicationsystems. Massive MIMO systems increase spectral efficiency by using a largenumber of antennas at the base station. Consequently, the signal processingat the base station has a high computational count. Paper-VI presents a configurable detection scheme which reduces this complexity by using techniquessuch as selective user detection and interpolation based signal processing. Hardware is optimized for resource sharing, resulting in a highly reconfigurable andenergy efficient uplink signal detector
Reduced complexity detection for massive MIMO-OFDM wireless communication systems
PhD ThesisThe aim of this thesis is to analyze the uplink massive multiple-input multipleoutput
with orthogonal frequency-division multiplexing (MIMO-OFDM) communication
systems and to design a receiver that has improved performance
with reduced complexity. First, a novel receiver is proposed for coded massive
MIMO-OFDM systems utilizing log-likelihood ratios (LLRs) derived
from complex ratio distributions to model the approximate effective noise
(AEN) probability density function (PDF) at the output of a zero-forcing
equalizer (ZFE). These LLRs are subsequently used to improve the performance
of the decoding of low-density parity-check (LDPC) codes and turbo
codes. The Neumann large matrix approximation is employed to simplify the
matrix inversion in deriving the PDF.
To verify the PDF of the AEN, Monte-Carlo simulations are used to demonstrate
the close-match fitting between the derived PDF and the experimentally
obtained histogram of the noise in addition to the statistical tests and
the independence verification. In addition, complexity analysis of the LLR
obtained using the newly derived noise PDF is considered. The derived LLR
can be time consuming when the number of receive antennas is very large
in massive MIMO-OFDM systems. Thus, a reduced complexity approximation
is introduced to this LLR using Newton’s interpolation with different
orders and the results are compared to exact simulations. Further simulation
results over time-flat frequency selective multipath fading channels demonstrated
improved performance over equivalent systems using the Gaussian
approximation for the PDF of the noise.
By utilizing the PDF of the AEN, the PDF of the signal-to-noise ratio (SNR)
is obtained. Then, the outage probability, the closed-form capacity and three
approximate expressions for the channel capacity are derived based on that
PDF. The system performance is further investigated by exploiting the PDF
of the AEN to derive the bit error rate (BER) for the massive MIMO-OFDM
system with different M-ary modulations. Then, the pairwise error probability
(PEP) is derived to obtain the upper-bounds for the convolutionally coded
and turbo coded massive MIMO-OFDM systems for different code generators
and receive antennas.
Furthermore, the effect of the fixed point data representation on the performance
of the massive MIMO-OFDM systems is investigated using reduced
detection implementations for MIMO detectors. The motivation for the fixed
point analysis is the need for a reduced complexity detector to be implemented
as an optimum massive MIMO detector with low precision. Different
decomposition schemes are used to build the linear detector based on
the IEEE 754 standard in addition to a user-defined precision for selected
detectors. Simulations are used to demonstrate the behaviour of several matrix
inversion schemes under reduced bit resolution. The numerical results
demonstrate improved performance when using QR-factorization and pivoted
LDLT decomposition schemes at reduced precision.Iraqi Government and the Iraqi
Ministry of Higher Education and Scientific researc
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