3,398 research outputs found
Pairwise Check Decoding for LDPC Coded Two-Way Relay Block Fading Channels
Partial decoding has the potential to achieve a larger capacity region than
full decoding in two-way relay (TWR) channels. Existing partial decoding
realizations are however designed for Gaussian channels and with a static
physical layer network coding (PLNC). In this paper, we propose a new solution
for joint network coding and channel decoding at the relay, called pairwise
check decoding (PCD), for low-density parity-check (LDPC) coded TWR system over
block fading channels. The main idea is to form a check relationship table
(check-relation-tab) for the superimposed LDPC coded packet pair in the
multiple access (MA) phase in conjunction with an adaptive PLNC mapping in the
broadcast (BC) phase. Using PCD, we then present a partial decoding method,
two-stage closest-neighbor clustering with PCD (TS-CNC-PCD), with the aim of
minimizing the worst pairwise error probability. Moreover, we propose the
minimum correlation optimization (MCO) for selecting the better
check-relation-tabs. Simulation results confirm that the proposed TS-CNC-PCD
offers a sizable gain over the conventional XOR with belief propagation (BP) in
fading channels.Comment: to appear in IEEE Trans. on Communications, 201
Turbo codes and turbo algorithms
In the first part of this paper, several basic ideas that prompted the coming of turbo codes are commented on. We then present some personal points of view on the main advances obtained in past years on turbo coding and decoding such as the circular trellis termination of recursive systematic convolutional codes and double-binary turbo codes associated with Max-Log-MAP decoding. A novel evaluation method, called genieinitialised iterative processing (GIIP), is introduced to assess the error performance of iterative processing. We show that using GIIP produces a result that can be viewed as a lower bound of the maximum likelihood iterative decoding and detection performance. Finally, two wireless communication systems are presented to illustrate recent applications of the turbo principle, the first one being multiple-input/multiple-output channel iterative detection and the second one multi-carrier modulation with linear precoding
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
Duality of Channel Encoding and Decoding - Part I: Rate-1 Binary Convolutional Codes
In this paper, we revisit the forward, backward and bidirectional
Bahl-Cocke-Jelinek-Raviv (BCJR) soft-input soft-output (SISO) maximum a
posteriori probability (MAP) decoding process of rate-1 binary convolutional
codes. From this we establish some interesting explicit relationships between
encoding and decoding of rate-1 convolutional codes. We observe that the
forward and backward BCJR SISO MAP decoders can be simply represented by their
dual SISO channel encoders using shift registers in the complex number field.
Similarly, the bidirectional MAP decoding can be implemented by linearly
combining the shift register contents of the dual SISO encoders of the
respective forward and backward decoders. The dual encoder structures for
various recursive and non-recursive rate-1 convolutional codes are derived.Comment: 32 pages, 20 figures, to appear in ET
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