5 research outputs found
Block-Orthogonal Space-Time Code Structure and Its Impact on QRDM Decoding Complexity Reduction
Full-rate space time codes (STC) with rate = number of transmit antennas have
high multiplexing gain, but high decoding complexity even when decoded using
reduced-complexity decoders such as sphere or QRDM decoders. In this paper, we
introduce a new code property of STC called block-orthogonal property, which
can be exploited by QR-decomposition-based decoders to achieve significant
decoding complexity reduction without performance loss. We show that such
complexity reduction principle can benefit the existing algebraic codes such as
Perfect and DjABBA codes due to their inherent (but previously undiscovered)
block-orthogonal property. In addition, we construct and optimize new full-rate
BOSTC (Block-Orthogonal STC) that further maximize the QRDM complexity
reduction potential. Simulation results of bit error rate (BER) performance
against decoding complexity show that the new BOSTC outperforms all previously
known codes as long as the QRDM decoder operates in reduced-complexity mode,
and the code exhibits a desirable complexity saturation property.Comment: IEEE Journal of Selected Topics in Signal Processing, Vol. 5, No. 8,
December 201
Construction of Block Orthogonal STBCs and Reducing Their Sphere Decoding Complexity
Construction of high rate Space Time Block Codes (STBCs) with low decoding
complexity has been studied widely using techniques such as sphere decoding and
non Maximum-Likelihood (ML) decoders such as the QR decomposition decoder with
M paths (QRDM decoder). Recently Ren et al., presented a new class of STBCs
known as the block orthogonal STBCs (BOSTBCs), which could be exploited by the
QRDM decoders to achieve significant decoding complexity reduction without
performance loss. The block orthogonal property of the codes constructed was
however only shown via simulations. In this paper, we give analytical proofs
for the block orthogonal structure of various existing codes in literature
including the codes constructed in the paper by Ren et al. We show that codes
formed as the sum of Clifford Unitary Weight Designs (CUWDs) or Coordinate
Interleaved Orthogonal Designs (CIODs) exhibit block orthogonal structure. We
also provide new construction of block orthogonal codes from Cyclic Division
Algebras (CDAs) and Crossed-Product Algebras (CPAs). In addition, we show how
the block orthogonal property of the STBCs can be exploited to reduce the
decoding complexity of a sphere decoder using a depth first search approach.
Simulation results of the decoding complexity show a 30% reduction in the
number of floating point operations (FLOPS) of BOSTBCs as compared to STBCs
without the block orthogonal structure.Comment: 16 pages, 7 figures; Minor changes in lemmas and construction
Revisited Design Criteria For STBCs With Reduced Complexity ML Decoding
The design of linear STBCs offering a low-complexity ML decoding using the
well known Sphere Decoder (SD) has been extensively studied in last years. The
first considered approach to derive design criteria for the construction of
such codes is based on the Hurwitz-Radon (HR) Theory for mutual orthogonality
between the weight matrices defining the linear code. This appproach served to
construct new families of codes admitting fast sphere decoding such as
multi-group decodable, fast decodable, and fast-group decodable codes. In a
second Quadratic Form approach, the Fast Sphere Decoding (FSD) complexity of
linear STBCs is captured by a Hurwitz Radon Quadratic Form (HRQF) matrix based
in its essence on the HR Theory. In this work, we revisit the structure of
weight matrices for STBCs to admit Fast Sphere decoding. We first propose novel
sufficient conditions and design criteria for reduced-complexity ML decodable
linear STBCs considering an arbitrary number of antennas and linear STBCs of an
arbitrary coding rate. Then we apply the derived criteria to the three families
of codes mentioned above and provide analytical proofs showing that the FSD
complexity depends only on the weight matrices and their ordering and not on
the channel gains or the number of antennas and explain why the so far used HR
theory-based approaches are suboptimal
A Survey on MIMO Transmission with Discrete Input Signals: Technical Challenges, Advances, and Future Trends
Multiple antennas have been exploited for spatial multiplexing and diversity
transmission in a wide range of communication applications. However, most of
the advances in the design of high speed wireless multiple-input multiple
output (MIMO) systems are based on information-theoretic principles that
demonstrate how to efficiently transmit signals conforming to Gaussian
distribution. Although the Gaussian signal is capacity-achieving, signals
conforming to discrete constellations are transmitted in practical
communication systems. As a result, this paper is motivated to provide a
comprehensive overview on MIMO transmission design with discrete input signals.
We first summarize the existing fundamental results for MIMO systems with
discrete input signals. Then, focusing on the basic point-to-point MIMO
systems, we examine transmission schemes based on three most important criteria
for communication systems: the mutual information driven designs, the mean
square error driven designs, and the diversity driven designs. Particularly, a
unified framework which designs low complexity transmission schemes applicable
to massive MIMO systems in upcoming 5G wireless networks is provided in the
first time. Moreover, adaptive transmission designs which switch among these
criteria based on the channel conditions to formulate the best transmission
strategy are discussed. Then, we provide a survey of the transmission designs
with discrete input signals for multiuser MIMO scenarios, including MIMO uplink
transmission, MIMO downlink transmission, MIMO interference channel, and MIMO
wiretap channel. Additionally, we discuss the transmission designs with
discrete input signals for other systems using MIMO technology. Finally,
technical challenges which remain unresolved at the time of writing are
summarized and the future trends of transmission designs with discrete input
signals are addressed.Comment: 110 pages, 512 references, submit to Proceedings of the IEE
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