460 research outputs found
Partial Enumerative Sphere Shaping
The dependency between the Gaussianity of the input distribution for the
additive white Gaussian noise (AWGN) channel and the gap-to-capacity is
discussed. We show that a set of particular approximations to the
Maxwell-Boltzmann (MB) distribution virtually closes most of the shaping gap.
We relate these symbol-level distributions to bit-level distributions, and
demonstrate that they correspond to keeping some of the amplitude bit-levels
uniform and independent of the others. Then we propose partial enumerative
sphere shaping (P-ESS) to realize such distributions in the probabilistic
amplitude shaping (PAS) framework. Simulations over the AWGN channel exhibit
that shaping 2 amplitude bits of 16-ASK have almost the same performance as
shaping 3 bits, which is 1.3 dB more power-efficient than uniform signaling at
a rate of 3 bit/symbol. In this way, required storage and computational
complexity of shaping are reduced by factors of 6 and 3, respectively.Comment: 6 pages, 6 figure
Probabilistic Shaping for Finite Blocklengths: Distribution Matching and Sphere Shaping
In this paper, we provide for the first time a systematic comparison of
distribution matching (DM) and sphere shaping (SpSh) algorithms for short
blocklength probabilistic amplitude shaping. For asymptotically large
blocklengths, constant composition distribution matching (CCDM) is known to
generate the target capacity-achieving distribution. As the blocklength
decreases, however, the resulting rate loss diminishes the efficiency of CCDM.
We claim that for such short blocklengths and over the additive white Gaussian
channel (AWGN), the objective of shaping should be reformulated as obtaining
the most energy-efficient signal space for a given rate (rather than matching
distributions). In light of this interpretation, multiset-partition DM (MPDM),
enumerative sphere shaping (ESS) and shell mapping (SM), are reviewed as
energy-efficient shaping techniques. Numerical results show that MPDM and SpSh
have smaller rate losses than CCDM. SpSh--whose sole objective is to maximize
the energy efficiency--is shown to have the minimum rate loss amongst all. We
provide simulation results of the end-to-end decoding performance showing that
up to 1 dB improvement in power efficiency over uniform signaling can be
obtained with MPDM and SpSh at blocklengths around 200. Finally, we present a
discussion on the complexity of these algorithms from the perspective of
latency, storage and computations.Comment: 18 pages, 10 figure
Probabilistic Constellation Shaping Algorithms: Performance vs. Complexity Trade-offs:Performance vs. Complexity Trade-offs
We review the recent advances in the design of probabilistic shaping algorithms. We investigate the implementation complexity of these algorithms in terms of required storage and computational power. We show that (1) the optimum performance can be achieved via different algorithms creating a trade-off between storage and computational complexities, and (2) a significant reduction in complexity can be achieved via the recently-proposed shift-based band-trellis enumerative sphere shaping if a slight degradation in performance is tolerated
On Probability Shaping for 5G MIMO Wireless Channel with Realistic LDPC Codes
Probability Shaping (PS) is a method to improve a Modulation and Coding
Scheme (MCS) in order to increase reliability of data transmission. It is
already implemented in some modern radio broadcasting and optic systems, but
not yet in wireless communication systems. Here we adapt PS for the 5G wireless
protocol, namely, for relatively small transport block size, strict complexity
requirements and actual low-density parity-check codes (LDPC). We support our
proposal by a numerical experiment results in Sionna simulator, showing 0.6 dB
gain of PS based MCS versus commonly used MCS.Comment: Paper contains 14 pages, 10 figures, 2 tables, comments are welcome!
Recommended for publication in Communications in Computer and Information
Scienc
On the Nonlinear Shaping Gain with Probabilistic Shaping and Carrier Phase Recovery
The performance of different probabilistic amplitude shaping (PAS)techniques in the nonlinear regime is investigated, highlighting its dependence on the PAS block length and the interaction with carrier phase recovery (CPR). Different PAS implementations are considered, based on different distribution matching (DM) techniques—namely, sphere shaping, shell mapping with different number of shells, and constant composition DM—and amplitude-to-symbol maps. When CPR is not included, PAS with optimal block length provides a nonlinear shaping gain with respect to a linearly optimized PAS (with infinite block length); among the considered DM techniques, the largest gain is obtained with sphere shaping. On the other hand, the nonlinear shaping gain becomes smaller, or completely vanishes, when CPR is included, meaning that in this case all the considered implementations achieve a similar performance for a sufficiently long block length. Similar results are obtained in different link configurations ( km, km, and km single-mode-fiber links), and also including laser phase noise, except when in-line dispersion compensation is used. Furthermore, we define a new metric, the nonlinear phase noise (NPN) metric, which is based on the frequency resolved logarithmic perturbation models and explains the interaction of CPR and PAS. We show that the NPN metric is highly correlated with the performance of the system. Our results suggest that, in general, the optimization of PAS in the nonlinear regime should always account for the presence of a CPR algorithm. In this case, the reduction of the rate loss (obtained by using sphere shaping and increasing the DM block length) turns out to be more important than the mitigation of the nonlinear phase noise (obtained by using constant-energy DMs and reducing the block length), the latter being already granted by the CPR algorithm
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