2,718 research outputs found
Space-time coding for UMTS. Performance evaluation in combination with convolutional and turbo coding
Space-time codes provide both diversity and coding gain when using multiple transmit antennas to increase spectral efficiency over wireless communications systems. Space-time block codes have already been included in the standardization process of UMTS in conjunction with conventional channel codes (convolutional and turbo codes). We discuss different encoding and decoding strategies when transmit diversity is combined with conventional channel codes, and present simulations results for the TDD and FDD modes of UTRA.Peer ReviewedPostprint (published version
High-Rate Space-Time Coded Large MIMO Systems: Low-Complexity Detection and Channel Estimation
In this paper, we present a low-complexity algorithm for detection in
high-rate, non-orthogonal space-time block coded (STBC) large-MIMO systems that
achieve high spectral efficiencies of the order of tens of bps/Hz. We also
present a training-based iterative detection/channel estimation scheme for such
large STBC MIMO systems. Our simulation results show that excellent bit error
rate and nearness-to-capacity performance are achieved by the proposed
multistage likelihood ascent search (M-LAS) detector in conjunction with the
proposed iterative detection/channel estimation scheme at low complexities. The
fact that we could show such good results for large STBCs like 16x16 and 32x32
STBCs from Cyclic Division Algebras (CDA) operating at spectral efficiencies in
excess of 20 bps/Hz (even after accounting for the overheads meant for pilot
based training for channel estimation and turbo coding) establishes the
effectiveness of the proposed detector and channel estimator. We decode perfect
codes of large dimensions using the proposed detector. With the feasibility of
such a low-complexity detection/channel estimation scheme, large-MIMO systems
with tens of antennas operating at several tens of bps/Hz spectral efficiencies
can become practical, enabling interesting high data rate wireless
applications.Comment: v3: Performance/complexity comparison of the proposed scheme with
other large-MIMO architectures/detectors has been added (Sec. IV-D). The
paper has been accepted for publication in IEEE Journal of Selected Topics in
Signal Processing (JSTSP): Spl. Iss. on Managing Complexity in Multiuser MIMO
Systems. v2: Section V on Channel Estimation is update
Generalized space-time shift keying designed for flexible diversity-, multiplexing- and complexity-tradeoffs
In this paper, motivated by the recent concept of Spatial Modulation (SM), we propose a novel Generalized Space-Time Shift Keying (G-STSK) architecture, which acts as a unified Multiple-Input Multiple-Output (MIMO) framework. More specifically, our G-STSK scheme is based on the rationale that P out of Q dispersion matrices are selected and linearly combined in conjunction with the classic PSK/QAM modulation, where activating P out of Q dispersion matrices provides an implicit means of conveying information bits in addition to the classic modem. Due to its substantial flexibility, our G-STSK framework includes diverse MIMO arrangements, such as SM, Space-Shift Keying (SSK), Linear Dispersion Codes (LDCs), Space-Time Block Codes (STBCs) and Bell Lab’s Layered Space-Time (BLAST) scheme. Hence it has the potential of subsuming all of them, when flexibly adapting a set of system parameters. Moreover, we also derive the Discrete-input Continuous-output Memoryless Channel (DCMC) capacity for our G-STSK scheme, which serves as the unified capacity limit, hence quantifying the capacity of the class of MIMO arrangements. Furthermore, EXtrinsic Information Transfer (EXIT) chart analysis is used for designing our G-STSK scheme and for characterizing its iterative decoding convergence
Iterative decoding for MIMO channels via modified sphere decoding
In recent years, soft iterative decoding techniques have been shown to greatly improve the bit error rate performance of various communication systems. For multiantenna systems employing space-time codes, however, it is not clear what is the best way to obtain the soft information required of the iterative scheme with low complexity. In this paper, we propose a modification of the Fincke-Pohst (sphere decoding) algorithm to estimate the maximum a posteriori probability of the received symbol sequence. The new algorithm solves a nonlinear integer least squares problem and, over a wide range of rates and signal-to-noise ratios, has polynomial-time complexity. Performance of the algorithm, combined with convolutional, turbo, and low-density parity check codes, is demonstrated on several multiantenna channels. The results for systems that employ space-time modulation schemes seem to indicate that the best performing schemes are those that support the highest mutual information between the transmitted and received signals, rather than the best diversity gain
Self-concatenated coding and multi-functional MIMO aided H.264 video telephony
Abstract— Robust video transmission using iteratively detected Self-Concatenated Coding (SCC), multi-dimensional Sphere Packing (SP) modulation and Layered Steered Space-Time Coding (LSSTC) is proposed for H.264 coded video transmission over correlated Rayleigh fading channels. The self-concatenated convolutional coding (SECCC) scheme is composed of a Recursive Systematic Convolutional (RSC) code and an interleaver, which is used to randomise the extrinsic information exchanged between the self-concatenated constituent RSC codes. Additionally, a puncturer is employed for improving the achievable bandwidth efficiency. The convergence behaviour of the MIMO transceiver advocated is investigated with the aid of Extrinsic Information Transfer (EXIT) charts. The proposed system exhibits an Eb /N0 gain of about 9 dB at the PSNR degradation point of 1 dB in comparison to the identical-rate benchmarker scheme
Iterative H.264 Source and Channel Decoding Using Sphere Packing Modulation Aided Layered Steered Space-Time Codes
The conventional two-stage turbo-detection schemes generally suffer from a Bit Error Rate (BER) floor. In this paper we circumvent this deficiency by proposing a three-stage turbo detected Sphere Packing (SP) modulation aided Layered Steered Space-Time Coding (LSSTC) scheme for H.264 coded video transmission over correlated Rayleigh fading channels. The soft-bit assisted H.264 coded bit-stream is protected using low-complexity short-block codes (SBCs), combined with a rate-1 recursive inner precoder is employed as an intermediate code which has an infinite impulse response and hence beneficially spreads the extrinsic information across the constituent decoders. This allows us to avoid having a BER floor. Additionally, the convergence behaviour of this serially concatenated scheme is investigated with the aid of Extrinsic Information Transfer (EXIT) Charts. The proposed system exhibits an Eb/N0 gain of about 12 dB in comparison to the benchmark scheme carrying out iterative source-channel decoding as well as Layered Steered Space-Time Coding (LSSTC) aided Sphere Packing (SP)demodulation, but dispensing with the optimised SBCs
Low-Complexity Detection/Equalization in Large-Dimension MIMO-ISI Channels Using Graphical Models
In this paper, we deal with low-complexity near-optimal
detection/equalization in large-dimension multiple-input multiple-output
inter-symbol interference (MIMO-ISI) channels using message passing on
graphical models. A key contribution in the paper is the demonstration that
near-optimal performance in MIMO-ISI channels with large dimensions can be
achieved at low complexities through simple yet effective
simplifications/approximations, although the graphical models that represent
MIMO-ISI channels are fully/densely connected (loopy graphs). These include 1)
use of Markov Random Field (MRF) based graphical model with pairwise
interaction, in conjunction with {\em message/belief damping}, and 2) use of
Factor Graph (FG) based graphical model with {\em Gaussian approximation of
interference} (GAI). The per-symbol complexities are and
for the MRF and the FG with GAI approaches, respectively, where
and denote the number of channel uses per frame, and number of transmit
antennas, respectively. These low-complexities are quite attractive for large
dimensions, i.e., for large . From a performance perspective, these
algorithms are even more interesting in large-dimensions since they achieve
increasingly closer to optimum detection performance for increasing .
Also, we show that these message passing algorithms can be used in an iterative
manner with local neighborhood search algorithms to improve the
reliability/performance of -QAM symbol detection
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