arXiv subjects

Gianluigi Liva

Publications and source records attributed to Gianluigi Liva.

94 records · Page 6Linked to original sources

arXiv2011

Turbo Codes Based on Time-Variant Memory-1 Convolutional Codes over Fq

Two classes of turbo codes over high-order finite fields are introduced. The codes are derived from a particular protograph sub-ensemble of the (dv=2,dc=3) low-density parity-check code ensemble. A first construction is derived as a parallel concatenation of two non-binary, time-variant accumulators. The second construction is based on the serial concatenation of a non-binary, time-variant differentiator and of a non-binary, time-variant accumulator, and provides a highly-structured flexible encoding scheme for (dv=2,dc=4) ensemble codes. A cycle graph representation is provided. The proposed codes can be decoded efficiently either as low-density parity-check codes (via belief propagation decoding over the codes bipartite graph) or as turbo codes (via the forward-backward algorithm applied to the component codes trellis). The forward-backward algorithm for symbol maximum a posteriori decoding of the component codes is illustrated and simplified by means of the fast Fourier transform. The proposed codes provide remarkable gains (~ 1 dB) over binary low-density parity-check and turbo codes in the moderate-short block regimes.

cs.IT↗

arXiv2011

High Throughput Random Access via Codes on Graphs: Coded Slotted ALOHA

In this paper, coded slotted ALOHA (CSA) is introduced as a powerful random access scheme to the MAC frame. In CSA, the burst a generic user wishes to transmit in the MAC frame is first split into segments, and these segments are then encoded through a local a packet-oriented code prior to transmission. On the receiver side, iterative interference cancellation combined with decoding of the local code is performed to recover from collisions. The new scheme generalizes the previously proposed irregular repetition slotted ALOHA (IRSA) technique, based on a simple repetition of the users' bursts. An interpretation of the CSA interference cancellation process as an iterative erasure decoding process over a sparse bipartite graph is identified, and the corresponding density evolution equations derived. Based on these equations, asymptotically optimal CSA schemes are designed for several rates and their performance for a finite number of users investigated through simulation and compared to IRSA competitors. Throughputs as high as 0.8 are demonstrated. The new scheme turns out to be a good candidate in contexts where power efficiency is required.

cs.IT↗

arXiv2010

High-Throughput Random Access via Codes on Graphs

Recently, contention resolution diversity slotted ALOHA (CRDSA) has been introduced as a simple but effective improvement to slotted ALOHA. It relies on MAC burst repetitions and on interference cancellation to increase the normalized throughput of a classic slotted ALOHA access scheme. CRDSA allows achieving a larger throughput than slotted ALOHA, at the price of an increased average transmitted power. A way to trade-off the increment of the average transmitted power and the improvement of the throughput is presented in this paper. Specifically, it is proposed to divide each MAC burst in k sub-bursts, and to encode them via a (n,k) erasure correcting code. The n encoded sub-bursts are transmitted over the MAC channel, according to specific time/frequency-hopping patterns. Whenever n-e>=k sub-bursts (of the same burst) are received without collisions, erasure decoding allows recovering the remaining e sub-bursts (which were lost due to collisions). An interference cancellation process can then take place, removing in e slots the interference caused by the e recovered sub-bursts, possibly allowing the correct decoding of sub-bursts related to other bursts. The process is thus iterated as for the CRDSA case.

cs.IT↗

arXiv2008

Low-Complexity LDPC Codes with Near-Optimum Performance over the BEC

Recent works showed how low-density parity-check (LDPC) erasure correcting codes, under maximum likelihood (ML) decoding, are capable of tightly approaching the performance of an ideal maximum-distance-separable code on the binary erasure channel. Such result is achievable down to low error rates, even for small and moderate block sizes, while keeping the decoding complexity low, thanks to a class of decoding algorithms which exploits the sparseness of the parity-check matrix to reduce the complexity of Gaussian elimination (GE). In this paper the main concepts underlying ML decoding of LDPC codes are recalled. A performance analysis among various LDPC code classes is then carried out, including a comparison with fixed-rate Raptor codes. The results show that LDPC and Raptor codes provide almost identical performance in terms of decoding failure probability vs. overhead.

cs.IT↗