  A distribution matcher (DM) maps a binary input sequence into a block of
nonuniformly distributed symbols. To facilitate the implementation of shaped
signaling, fast DM solutions with high throughput and low serialism are
required. We propose a novel DM architecture with parallel amplitudes (PADM)
for which m component DMs, each with a different binary output alphabet, are
operated in parallel in order to generate a shaped sequence with m amplitudes.
With negligible rate loss compared to a single nonbinary DM, PA-DM has a
parallelization factor that grows linearly with m, and the component DMs have
reduced output lengths. For such binary-output DMs, a novel
constant-composition DM (CCDM) algorithm based on subset ranking (SR) is
proposed. We present SR-CCDM algorithms that are serial in the minimum number
of occurrences of either binary symbol for mapping and fully parallel in
demapping. For distributions that are optimized for the additive white Gaussian
noise (AWGN) channel, we numerically show that PA-DM combined with SR-CCDM can
reduce the number of sequential processing steps by more than an order of
magnitude, while having a rate loss that is comparable to conventional
nonbinary CCDM with arithmetic coding.
