959 research outputs found
Precoded Integer-Forcing Universally Achieves the MIMO Capacity to Within a Constant Gap
An open-loop single-user multiple-input multiple-output communication scheme
is considered where a transmitter, equipped with multiple antennas, encodes the
data into independent streams all taken from the same linear code. The coded
streams are then linearly precoded using the encoding matrix of a perfect
linear dispersion space-time code. At the receiver side, integer-forcing
equalization is applied, followed by standard single-stream decoding. It is
shown that this communication architecture achieves the capacity of any
Gaussian multiple-input multiple-output channel up to a gap that depends only
on the number of transmit antennas.Comment: to appear in the IEEE Transactions on Information Theor
Error Rate Analysis of GF(q) Network Coded Detect-and-Forward Wireless Relay Networks Using Equivalent Relay Channel Models
This paper investigates simple means of analyzing the error rate performance
of a general q-ary Galois Field network coded detect-and-forward cooperative
relay network with known relay error statistics at the destination. Equivalent
relay channels are used in obtaining an approximate error rate of the relay
network, from which the diversity order is found. Error rate analyses using
equivalent relay channel models are shown to be closely matched with simulation
results. Using the equivalent relay channels, low complexity receivers are
developed whose performances are close to that of the optimal maximum
likelihood receiver.Comment: 28 pages, 10 figures. This work has been submitted to the IEEE for
possible publication. Copyright may be transferred without notice, after
which this version may no longer be accessibl
Impact of wireless channel uncertainty upon M-ary distributed detection systems.
We consider a wireless sensor network (WSN), consisting of several sensors and a fusion center (FC), which is tasked with solving an -ary hypothesis testing problem. Sensors make -ary decisions and transmit their digitally modulated decisions over orthogonal channels, which are subject to Rayleigh fading and noise, to the FC. Adopting Bayesian optimality criterion, we consider training and non-training based distributed detection systems and investigate the effect of imperfect channel state information (CSI) on the optimal maximum a posteriori probability (MAP) fusion rules and detection performance, when the sum of training and data symbol transmit powers is fixed. Our results show that for Rayleigh fading channel, when sensors employ -FSK or binary FSK (BFSK) modulation, the error probability is minimized when training symbol transmit power is zero (regardless of the reception mode at the FC). However, for coherent reception, -PSK and binary PSK (BPSK) modulation the error probability is minimized when half of transmit power is allocated for training symbol. If the channel is Rician fading, regardless of the modulation, the error probability is minimized when training transmit power is zero
On the Asymptotic Performance of Bit-Wise Decoders for Coded Modulation
Two decoder structures for coded modulation over the Gaussian and flat fading
channels are studied: the maximum likelihood symbol-wise decoder, and the
(suboptimal) bit-wise decoder based on the bit-interleaved coded modulation
paradigm. We consider a 16-ary quadrature amplitude constellation labeled by a
Gray labeling. It is shown that the asymptotic loss in terms of pairwise error
probability, for any two codewords caused by the bit-wise decoder, is bounded
by 1.25 dB. The analysis also shows that for the Gaussian channel the
asymptotic loss is zero for a wide range of linear codes, including all
rate-1/2 convolutional codes
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
Signal mapping designs for bit-interleaved coded modulation with iterative decoding (BICM-ID)
Bit-interleaved coded modulation with iterative decoding (BICM-ID)is a spectral efficient coded modulation technique to improve the performance of digital communication systems. It has been widely known that for fixed signal constellation, interleaver and error control code, signal mapping plays an important role in
determining the error performance of a BICM-ID system. This thesis concentrates on signal mapping designs for BICM-ID systems. To this end, the distance criteria to find the best mapping in terms of the asymptotic performance are first analytically derived for different channel models. Such criteria are then used to find good mappings for various two-dimensional
8-ary constellations. The usefulness of the proposed mappings of 8-ary constellations is verified by both the error floor bound and simulation results.
Moreover, new mappings are also proposed for BICM-ID systems employing the quadrature phase shift keying (QPSK) constellation. The new mappings are obtained by considering many QPSK symbols over a multiple symbol interval, which essentially creates hypercube constellations. Analytical and simulation results show that the use of the proposed
mappings together with very simple convolutional codes can offer significant coding gains over the conventional BICM-ID systems for all the channel models considered. Such coding gains are
achieved without any bandwidth nor power expansion and with a very small increase in the system complexity
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