14,782 research outputs found
Spatial Coded Modulation
In this paper, we propose a spatial coded modulation (SCM) scheme, which
improves the accuracy of the active antenna detection by coding over the
transmit antennas. Specifically, the antenna activation pattern in the SCM
corresponds to a codeword in a properly designed codebook with a larger minimum
Hamming distance than its counterpart conventional spatial modulation. As the
minimum Hamming distance increases, the reliability of the active antenna
detection is directly enhanced, which in turn improves the demodulation of the
modulated symbols and yields a better system reliability. In addition to the
reliability, the proposed SCM scheme also achieves a higher capacity with the
identical antenna configuration compared to the conventional spatial modulation
technique. Moreover, the proposed SCM scheme strikes a balance between spectral
efficiency and reliability by trading off the minimum Hamming distance with the
number of available codewords. The optimal maximum likelihood detector is first
formulated. Then, a low-complexity suboptimal detector is proposed to reduce
the computational complexity, which has a two-step detection. Theoretical
derivations of the channel capacity and the bit error rate are presented in
various channel scenarios, i.e., Rayleigh, Rician, Nakagami-m, imperfect
channel state information, and spatial correlation. Further derivation on
performance bounding is also provided to reveal the insight of the benefit of
increasing the minimum Hamming distance. Numerical results validate the
analysis and demonstrate that the proposed SCM outperforms the conventional
spatial modulation techniques in both channel capacity and system reliability.Comment: 30 pages, 17 figure
Bounds on List Decoding of Rank-Metric Codes
So far, there is no polynomial-time list decoding algorithm (beyond half the
minimum distance) for Gabidulin codes. These codes can be seen as the
rank-metric equivalent of Reed--Solomon codes. In this paper, we provide bounds
on the list size of rank-metric codes in order to understand whether
polynomial-time list decoding is possible or whether it works only with
exponential time complexity. Three bounds on the list size are proven. The
first one is a lower exponential bound for Gabidulin codes and shows that for
these codes no polynomial-time list decoding beyond the Johnson radius exists.
Second, an exponential upper bound is derived, which holds for any rank-metric
code of length and minimum rank distance . The third bound proves that
there exists a rank-metric code over \Fqm of length such that the
list size is exponential in the length for any radius greater than half the
minimum rank distance. This implies that there cannot exist a polynomial upper
bound depending only on and similar to the Johnson bound in Hamming
metric. All three rank-metric bounds reveal significant differences to bounds
for codes in Hamming metric.Comment: 10 pages, 2 figures, submitted to IEEE Transactions on Information
Theory, short version presented at ISIT 201
Achievable Information Rates for Coded Modulation with Hard Decision Decoding for Coherent Fiber-Optic Systems
We analyze the achievable information rates (AIRs) for coded modulation
schemes with QAM constellations with both bit-wise and symbol-wise decoders,
corresponding to the case where a binary code is used in combination with a
higher-order modulation using the bit-interleaved coded modulation (BICM)
paradigm and to the case where a nonbinary code over a field matched to the
constellation size is used, respectively. In particular, we consider hard
decision decoding, which is the preferable option for fiber-optic communication
systems where decoding complexity is a concern. Recently, Liga \emph{et al.}
analyzed the AIRs for bit-wise and symbol-wise decoders considering what the
authors called \emph{hard decision decoder} which, however, exploits \emph{soft
information} of the transition probabilities of discrete-input discrete-output
channel resulting from the hard detection. As such, the complexity of the
decoder is essentially the same as the complexity of a soft decision decoder.
In this paper, we analyze instead the AIRs for the standard hard decision
decoder, commonly used in practice, where the decoding is based on the Hamming
distance metric. We show that if standard hard decision decoding is used,
bit-wise decoders yield significantly higher AIRs than symbol-wise decoders. As
a result, contrary to the conclusion by Liga \emph{et al.}, binary decoders
together with the BICM paradigm are preferable for spectrally-efficient
fiber-optic systems. We also design binary and nonbinary staircase codes and
show that, in agreement with the AIRs, binary codes yield better performance.Comment: Published in IEEE/OSA Journal of Lightwave Technology, 201
Communication Complexity of Permutation-Invariant Functions
Motivated by the quest for a broader understanding of communication
complexity of simple functions, we introduce the class of
"permutation-invariant" functions. A partial function is permutation-invariant if for every bijection
and every , it is the case that . Most of the commonly studied functions
in communication complexity are permutation-invariant. For such functions, we
present a simple complexity measure (computable in time polynomial in given
an implicit description of ) that describes their communication complexity
up to polynomial factors and up to an additive error that is logarithmic in the
input size. This gives a coarse taxonomy of the communication complexity of
simple functions. Our work highlights the role of the well-known lower bounds
of functions such as 'Set-Disjointness' and 'Indexing', while complementing
them with the relatively lesser-known upper bounds for 'Gap-Inner-Product'
(from the sketching literature) and 'Sparse-Gap-Inner-Product' (from the recent
work of Canonne et al. [ITCS 2015]). We also present consequences to the study
of communication complexity with imperfectly shared randomness where we show
that for total permutation-invariant functions, imperfectly shared randomness
results in only a polynomial blow-up in communication complexity after an
additive overhead
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