"Amplify and Forward" and "Decode and Forward" are the two main relaying functions that have been proposed since the advent of cooperative communication. "\textit{Soft} Decode and Forward" is a recently introduced relaying principle that is to combine the benefits of the classical two relaying algorithms. In this work, we thoroughly investigate \textit{soft} relaying algorithms when convolutional or turbo codes are applied. We study the error performance of two cooperative scenarios employing soft-relaying. A novel approach, the mutual information loss due to data processing, is proposed to analyze the relay-based soft encoder. We also introduce a novel approach to derive the estimated bit error rate and the equivalent channel SNR for the relaying techniques considered in the paper.
To improve the sum-rate (SR) of the dual-hop relay system, a novel two-stage power allocation scheme with non-orthogonal multiple access (NOMA) is proposed. In this scheme, after the reception of the superposition coded symbol with a power allocation from the source, the relay node forwards a new superposition coded symbol with another power allocation to the destination. By employing the maximum ratio combination (MRC), the destination jointly decodes the information symbols from the source and the relay. Assuming Rayleigh fading channels, closed-form solution of the ergodic SR at high signal…
The compute-and-forward (CAF) scheme has attracted great interests due to its high band-width efficiency on two-way relay channels. In the CAF scheme, a relay attempts to decode a linear combination of transmitted messages from other terminals or relays. It is a crucial issue to study practical error-correcting codes in order to realize the CAF scheme with low computational complexity. In this paper, we present an efficient bit-interleaved coded modulation (BICM) scheme for the CAF scheme with phase shift keying (PSK) modulations. In particular, we examine the asymptotic decoding performance o…
In this work we develop the maximum likelihood detection (MLD) algorithm for noncoherent amplitude shift keying (NCASK) systems in additive white Gaussian noise (AWGN) channels. The developed algorithm was used to investigate the performance of the NCASK system with convolutional coding and soft-decision Viterbi decoding. Tight and simple upper bounds have been derived to describe the system performance; simulation results have shown that the derived upper bounds are within 0.1 dB of the simulated points.
Analog network coding (ANC) is a throughput increasing technique for the two-way relay channel (TWRC) whereby two end nodes transmit simultaneously to a relay at the same time and band, followed by the relay broadcasting the received sum of signals to the end nodes. Coherent reception under ANC is challenging due to requiring oscillator synchronization for all nodes, a problem further exacerbated by Doppler shift. This work develops a noncoherent M-ary frequency-shift keyed (FSK) demodulator implementing ANC. The demodulator produces soft outputs suitable for use with capacity-approaching chan…
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…
Fourier-Curve Constellations under Tangential Perturbation: Covariance-Aware Soft Demapping on Coded Links
RPTU University Kaiserslautern-Landau(凯泽斯劳滕-兰道技术大学);Beijing Huairou Laboratory(北京怀柔实验室);Princeton University(普林斯顿大学);German Research Center for Artificial Intelligence (DFKI)(德国人工智能研究中心)
Mitsubishi Electric Research Laboratories (MERL)(三菱电机研究实验室);Yokohama National University(横滨国立大学)
This paper studies a new application of deep learning (DL) for optimizing constellations in two-way relaying with physical-layer network coding (PNC), where deep neural network (DNN)-based modulation and demodulation are employed at each terminal and relay node. We train DNNs such that the cross entropy loss is directly minimized, and thus it maximizes the likelihood, rather than considering the Euclidean distance of the constellations. The proposed scheme can be extended to higher level constellations with slight modification of the DNN structure. Simulation results demonstrate a significant …
We propose a novel soft-output joint channel estimation and data detection (JED) algorithm for multiuser (MU) multiple-input multiple-output (MIMO) wireless communication systems. Our algorithm approximately solves a maximum a-posteriori JED optimization problem using deep unfolding and generates soft-output information for the transmitted bits in every iteration. The parameters of the unfolded algorithm are computed by a hyper-network that is trained with a binary cross entropy (BCE) loss. We evaluate the performance of our algorithm in a coded MU-MIMO system with 8 basestation antennas and 4…