Joint channel decoding with feedback power control in sensor networks with correlated sources

In this paper, we focus on the design of optimized binary convolutional codes (CCs) and serially concatenated convolutional codes (SCCCs) in the presence of a-priori information (API) at the receiver. For large signal-to-noise ratios (SNRs), we first propose a CC design criterion based on the minimization of a union bound on the bit error probability (BEP). In this case, relevant performance gains, with respect to previously proposed CCs, are obtained. These gains persist even in the presence of estimation errors on the API. Then, we apply the same union bound-based design criterion to SCCCs. Since the BEP of SCCCs is characterized by a typical waterfall shape, the proposed union bound-based design criterion is accurate only at large SNR, to estimate the BEP floor. In order to complement this analysis, we propose a density evolution-based approach to optimize the SCCC design in terms of minimization of the SNR of the knee of the BEP curve. The obtained simulation results show substantial gains with respect to previously proposed parallel concatenated convolutional coding (PCCCing) schemes optimized under the assumption of no API at the decoder. Moreover, in the presence of strong API the proposed SCCCs allow to approach the Shannon limit (SL) more than any previously proposed turbo coding scheme.

Turbo codes are attractive compared with Low Density Parity Check (LDPC) codes for Forward Error Correction (FEC) applications mainly due to their superior performance, especially at low Signal-to-Noise Ratio (SNR) such as are common in Powerline channels. For example, IEEE 1901-FFT PHY used the Turbo coding scheme defined in the HomePlug AV standards. However, patent fees are usually required for each turbo-code enabled manufactured device. The objective of this paper is to examine whether unlicensed LDPC codes, with optimized choices of block lengths, could be a viable alternative for future Powerline Communications (PLC) applications. The paper shows that the performance of the LDPC codes can approximate that of the Turbo codes with higher block lengths, on channels with typical and realistic PLC characteristics. The paper also shows that the additional complexity associated with this increase in block length can be mitigated by the use of Quasi-Cyclic LDPC (QC-LDPC) codes.

International audience

Terrestrial digital multimedia TV/handle broadcasting (DMB-TH) is a newly upcoming framing structure, channel coding and modulation for digital television terrestrial broadcasting system standard of China, which is recently drafted and is ready to be verified in order to deploy mobile multimedia broadcasting services for the public. The adoption of strong channel coding techniques appears to be of key importance for mobile operators and broadcasters. Low-density parity-check (LDPC) codes have been widely considered as error-correcting codes for next generation communication systems. A good LDPC decoder design requires both implementation friendly LDPC codes and efficient decoder architectures. The quality of LDPC code is crucial in determining the coding gain and implementation complexity of LDPC hardware decoders. This paper presents a turbo-decoding message-passing algorithm (TDMP) based LDPC code search algorithm with hardware considerations. The main advantages of the proposed algorithm over the DMB-TH standard decoding algorithm are 1) improvement in coding gain by an order of magnitude at high signal-to-noise ratio (SNR), 2) reduced decoder complexity. The performance of the proposed TDMP architecture is shown by the comparison of simulation results.

A method by which a popular signal-to-noise ratio (SNR) estimator can be reconfigured to yield improved performance is proposed. The reconfiguration consists of partitioning the symbol interval into a larger (but even) number of subdivisions than the two that have been traditionally suggested for this estimator but still processing the observables in successive pairs. The optimum number of subdivisions is shown to depend on the SNR range in which the true SNR lies; however, we also show that these SNR regions can be significantly widened with very little loss in performance. Most important is the fact that with this reconfiguration, the SNR estimator tracks the Cramer-Rao bound on the variance of the estimator over the entire range of SNR values.

This work studies the performance of a cooperative network which consists of two channel-coded sources, multiple relays, and one destination. To achieve high spectral efficiency, we assume that a single time slot is dedicated to relaying. Conventional network-coded-based cooperation (NCC) selects the best relay which uses network coding to serve the two sources simultaneously. The bit error rate (BER) performance of NCC with channel coding, however, is still unknown. In this paper, we firstly study the BER of NCC via a closed-form expression and analytically show that NCC only achieves diversity of order two regardless of the number of available relays and the channel code. Secondly, we propose a novel partial relaying-based cooperation (PARC) scheme to improve the system diversity in the finite signal-to-noise ratio (SNR) regime. In particular, closed-form expressions for the system BER and diversity order of PARC are derived as a function of the operating SNR value and the minimum distance of the channel code. We analytically show that the proposed PARC achieves full (instantaneous) diversity order in the finite SNR regime, given that an appropriate channel code is used. Finally, numerical results verify our analysis and demonstrate a large SNR gain of PARC over NCC in the SNR region of interest.

This paper explains the structure of a newly designed quarter-rate low density parity check (LDPC) code for the cloud transmission system, and presents its truncated performance under additive white Gaussian noise (AWGN) channel. Since new quarter-rate LDPC code has fountain code's property, at the receiver, it can be decoded with truncated codeword for power saving and less latency under high signal to noise ratio (SNR) regions. By computer simulation, the truncated LDPC code shows the same or worse performance compared with the dedicated DVB-T2/S2 LDPC code.

A BP-based algorithm with 2-dimensional classified normalized correction is developed to reduce the complexity and improve the performance of decoding algorithm for the low density parity check (LDPC) codes. The algorithm first utilizes classification according to the absolute values of incoming messages in check nodes. Then it uses 2-dimensional normalization to correct the minimum and sub-minimum values. The 2-dimensional normalized factors can be calculated respectively by using probability and statistic theory in the initialization step. Simulation results illustrate that the proposed algorithm achieves better performance in bit error ratio (BER) and average iteration number than normalized BP-based algorithm in the high signal noise ratio (SNR) region, i.e., it can achieve 0.4 dB SNR gain and reduce 20% number of iterations at BER= 5 10  , whose complexity is also much less than that of belief propagation (BP) algorithm. It is concluded that the proposed algorithm offers better tradeoff between performance and complexity.  Index Terms—channel coding theory, density evolution, Iterative decoding algorithm

One of the key weaknesses of low-density parity-check (LDPC) codes is the error floor that they typically exhibit at high signal-to-noise ratios (SNRs). Such an error floor is usually attributed to problematic structures known as trapping sets (TSs). The overwhelming majority of existing error floor estimation schemes consider the case of binary phase shift keying (BPSK) signalling. Unfortunately, these schemes are not readily extensible to estimate the error floor of high order LDPC coded modulation systems considered herein. To provide such a scheme, in this work, we use mean-shift importance sampling (MS-IS) to develop a novel error floor estimation methodology for high-order pulse amplitude modulation (PAM) and quadrature amplitude modulation (QAM) LDPC coded systems. First, a computationally efficient graphical-based approach is used to identify the TSs of a given LDPC code. Subsequently, a novel analytical approach is devised to identify the TSs that are likely to have a higher contribution in the error floor. These TSs are referred to as potentially dominant TSs (PDTSs). Finally, a new methodology for categorizing the PDTSs into equivalence classes is developed. A representative PDTS of each equivalence class is chosen and an MS-IS framework is devised to obtain the error rate corresponding to each equivalence class. To arrive at the desired MS-IS scheme, we develop an algorithm that invokes the geometry of the constellation to determine the MS value. In contrast with the conventional MS-IS method used in BPSK signalling, in the proposed MS-IS scheme, the MS value is a variable that is determined based on the TS and the transmitted codeword. The computational complexity of the three main steps of our methodology, viz. extracting the PDTSs, determining the MS values, and applying the MS-IS scheme, depends merely on the size of the constellation and the structure of the code, but not on the SNR. Numerical simulations confirm the efficacy and accuracy of the proposed technique at different SNRs.

This work studies the performance of a cooperative network which consists of two channel-coded sources, multiple relays, and one destination. Due to the spectral efficiency constraint, we assume that a single time slot is dedicated to relaying. Conventional network-coded based cooperation (NCC) selects the best relay which uses network coding to serve the two sources simultaneously. It is shown that NCC, however, only achieves diversity of order two regardless of the number of available relays and the channel code. In this paper, we propose a novel partial relaying based cooperation (PARC) scheme to improve the system diversity in the finite signal-to-noise ratio (SNR) regime. Firstly, closed-form expressions for the system bit error rate (BER) and diversity order of PARC are derived as a function of the operating SNR value and the minimum distance of the channel code. Secondly, we analytically show that the proposed PARC achieves full diversity order in the finite SNR regime, given that an appropriate channel code is used. Finally, numerical results verify our analysis and demonstrate a large SNR gain of PARC over NCC in the SNR region of interest.

In this paper, we apply simulation-based optimization methods to detect quadrature amplitude modulated (QAM) MIMO signals. The first one is the so-called Cross-Entropy (CE) method which enables the corresponding CE-based detector to provide bit-error-rate (BER) performance close to that achievable by the maximum-likelihood (ML) detector when the signal-to-noise ratio (SNR) is relatively low. Unfortunately, the performance curves exhibit error floors in the high SNR region. To improve the performance in the high SNR region, we borrow the concept of Particle Swarm Optimization (PSO) and refer to the resulting iterative detector as the Particle-Swarm-driven Cross-Entropy (PSD-CE) MIMO detector. This detector gives a significant BER performance improvement in the medium-to-high SNR region. We also consider the case when the channel state information is imperfect and suggest a robust detector structure based on a modified score function.

The high throughput with low latency, massively connected devices, and effective utilization of spectrum for current wireless communication systems can be realized by adopting the fifth-generation (5G) new radio (NR) air interface. The key remarkable features that 5G NR presents are Ultra-Reliable Low-Latency Communications (URLLC), enhanced Mobile Broadband (eMBB), and massive Machine Type Communications (mMTC). To meet thereof features, 5G NR exerts different multiple access and modulation techniques. This paper addresses the physical layer of 5G NR and more explicitly explores the transmission of 5G NR over the physical uplink shared channel (PUSCH) considering several parameters. For example, different sub-carrier spacings (SCSs) are taken into account for analyzing the performance of PUSCH in terms of throughput versus Signal-to-Noise Ratio (SNR). Moreover, the effect of the well-known modulation techniques such as Quadrature Phase Shift Keying (QPSK), different order of Quadrature Amplitude Modulation (QAM) (i.e., 16, 64, and 256) on throughput is studied. Later on, the number of base station (BS) and user equipment (UE) antennas are varied. Lastly, the performance of PUSCH over different propagation channel models (clustered delay line (CDL) and tap delay line (TDL)) is also investigated in this paper. The extensive simulation studies have proved that QPSK exhibits finer outcomes in low SNR regions while 256-QAM shows remarkable results in high SNR regions. The maximum throughput can be realized even in low SNR regime if the number of BS antennas is increased. In addition, high throughput value can be attained by increasing SCS.

In this paper, we investigate the impact of channel coding on two kinds of non-orthogonal multiple access (NOMA) schemes, either with a successive interference cancellation (SIC) receiver or with a joint decoding (JD) receiver. Firstly, the information-theoretic individual achievable signal-to-noise ratio (SNR) regions of SIC and JD are analyzed. Then single-user-oriented (SU) code and multi-users-oriented (MU) code are considered for SIC and JD, and the practical individual achievable SNR regions of SIC and JD with these two kinds of channel codes are obtained, which provides an intuitive way to evaluate system performance under different channel conditions and transmission rates. Simulation results show that, the practical boundaries of individual achievable SNR region of SIC generally lie inside the boundaries of JD, as predicted by the theoretical analysis. Moreover, SU code, which is capacity-approaching over point-to-point channel, performs better than MU code for SIC, while the choice of channel codes for JD depends on transmission rates and channel conditions.

Adaptive coded modulation (ACM) is a key technique to increase spectral as well as power efficiency for orthogonal frequency division multiplexing (OFDM) systems. In this paper, an efficient rate adaptive low density parity check (LDPC) coded modulation (RALCM) algorithm is proposed, which maximizes the payload rate for OFDM systems under the constraint of the given transmit power and the target bit error rate (BER). Taking advantage of the two dimensional look up table for the signal to noise ratio (SNR) thresholds, the RALCM algorithm assigns different combinations of the LDPC code rates and quadrature amplitude modulation (QAM) modulations for subcarriers according to the channel frequency response (CFR). Both theoretical analysis and computer simulation show that the proposed algorithm not only efficiently improves the payload rate of the LDPC coded OFDM system over frequency selective fading channels, but also inherently reduces the computational complexity of the system optimization.

Multiple-Input and Multiple-Output, or MIMO is the use of multiple antennas at both the transmitter and receiver to improve communication performance. MIMO technology has attracted attention in wireless communications; because it offers significant increases in data throughput and spectral efficiency without additional bandwidth or increased transmit power. To achieve the mentioned above performance Bit Error Rates (BER) should be low. For this reason efficient encoding and decoding algorithms should be used. MIMO systems rely on error-control coding to ensure reliable communication in the presence of noise. Forward Error Correction Codes (FEC) such as convolutional and block codes were investigated for MIMO systems. Low Density Parity Check (LDPC) shows good performance except that an error floor may appear at high Signal to Noise Ratio (SNR). In this work we propose a concatenated error control code that reduces the error floor of LDPC codes suffering from error floor. The proposed scheme is a good candidate for high rates real time communication since it reduces the decoding latency as well.