Sparse Network Coding (SNC) has been a promising network coding scheme as an improvement for Random Linear Network Coding (RLNC) in terms of the computational complexity. However, in this literature, there has been no analytical expressions for the probability of decoding a fraction of source messages after transmission of some coded packets. In this work, we looked into the problem of the probability of decoding a fraction of source messages, i.e., partial decoding, in the decoder for a system which uses SNC. We exploited the Principle of Inclusion and Exclusion to derive expressions of partial decoding probability. The presented model predicts the probability of partial decoding with an average deviation of 6 . Our results show that SNC has a great potential for recovering a fraction of the source message, especially in higher sparsity and lower Galois Field size. Moreover, to achieve a better probability of partial decoding throughout transmissions, we define a sparsity tuning scheme that significantly increases the probability of partial decoding. Our results show that this tuning scheme achieves a 16 improvement in terms of probability of decoding a fraction of source packets with respect to traditional SNC.
The authors of @cite_13 and @cite_19 introduced and analyzed an improvement for the SNC scheme called perpetual coding. However, this coding scheme is not completely random and uses a structured type of coding to send packets, and the analysis on this coding scheme can not be extended to random SNC scheme, which is the scope of this paper.
@cite_19 @cite_13
2017096524 1575671689 2564688069 1993626808
We investigate a channel-coded physical-layer network coding (CPNC) scheme for binary-input Gaussian two-way relay channels. In this scheme, the codewords of the two users are transmitted simultaneously. The relay computes and forwards a network-coded (NC) codeword without complete decoding of the two users' individual messages. We propose a new punctured codebook method to explicitly find the distance spectrum of the CPNC scheme. Based on that, we derive an asymptotically tight performance bound for the error probability. Our analysis shows that, compared to the single-user scenario, the CPNC scheme exhibits the same minimum Euclidean distance but an increased multiplicity of error events with minimum distance. At a high SNR, this leads to an SNR penalty of at most ln2 (in linear scale), for long channel codes of various rates. Our analytical results match well with the simulated performance. We propose and design a practical modulation-coded (MC) physical-layer network coding (PNC) scheme to approach the capacity limits of Gaussian and fading two-way relay channels (TWRCs). In the proposed scheme, an irregular repeat–accumulate (IRA) MC over @math with the same random coset is employed at two users, which directly maps the message sequences into coded PAM or QAM symbol sequences. The relay chooses appropriate network coding coefficients and computes the associated finite-field linear combinations of the two users' message sequences using an iterative belief propagation algorithm. For a symmetric Gaussian TWRC, we show that, by introducing the same random coset vector at the two users and a time-varying accumulator in the IRA code, the MC-PNC scheme exhibits symmetry and permutation-invariant properties for the soft information distribution of the network-coded message sequence (NCMS). We explore these properties in analyzing the convergence behavior of the scheme and optimizing the MC to approach the capacity limit of a TWRC. For a block fading TWRC, we present a new MC linear PNC scheme and an algorithm used at the relay for computing the NCMS. We demonstrate that our developed schemes achieve near-capacity performance in both Gaussian and Rayleigh fading TWRCs. For example, our designed codes over GF(7) and GF(3) with a code rate of 3 4 are within 1 and 1.2 dB of the TWRC capacity, respectively. Our method can be regarded as a practical embodiment of the notion of compute-and-forward with a good nested lattice code, and it can be applied to a wide range of network configurations. Perpetual codes provide a sparse, but structured coding for fast encoding and decoding. In this work, we illustrate that perpetual codes introduce linear dependent packet transmissions in the presence of an erasure channel. We demonstrate that the number of linear dependent packet transmissions is highly dependent on a parameter called the width ( ( )), which represents the number of consecutive non-zero coding coefficient present in each coded packet after a pivot element. We provide a mathematical analysis based on the width of the coding vector for the number of transmitted packets and validate it with simulation results. The simulations show that for ( = 5 ), generation size (g = 256 ), and low erasure probability on the link, a destination can receive up to (70 ) overhead in average. Moreover, increasing the width, the overhead contracts, and for ( 60 ) it becomes negligible. We study a new linear physical-layer network coding (LPNC) scheme for fading two-way relay channels. In the uplink phase, two users transmit simultaneously. The relay selects some integer coefficients and computes a linear combination (in a size-q finite set) of the two users' messages, which is broadcast in the downlink phase. We develop a design criterion for choosing the integer coefficients that minimizes the error probability. Based on that, we derive an asymptotically tight bound, in a closed-form, for the error probability of the LPNC scheme over Rayleigh fading channels. Our analysis shows that the error-rate performance of the LPNC scheme becomes asymptotically optimal at a high SNR, and our designed LPNC scheme significantly outperforms existing schemes in the literature.