Irregular Convolutional Code Research Articles

Design and Analysis of Joint Source-Channel Code System with Fixed-Length Code

As the demands of multimedia and data services increase, efficient communication systems are being investigated to meet the high data rate requirements. Joint source-channel coding (JSCC) schemes were proposed for improving overall system performance. However, existing JSCC systems may suffer a symbol error rate (SER) performance loss when residual source redundancy is not fully exploited. This paper presents a novel, low-complexity JSCC system, which consists of a fixed-length source block code and an irregular convolutional channel code. A simple approach is proposed to design source codes that minimize the SER of source detection and guarantee the convergence of iterative source-channel decoding (ISCD). To improve the waterfall performance of ISCD, the channel code is optimized by using the extrinsic information transfer (EXIT) chart and the concept of irregular code. The channel code is constituted by recursive non-systematic convolutional (RNSC) subcodes. The weights of subcodes are optimized to make the EXIT curves of the channel decoder and the source decoder well-matched, and therefore, a near-capacity performance is achieved. Simulation results show that the proposed system achieves more than 1 dB gains and 0.3 dB gains compared to the separate source-channel code system and the other optimal JSCC systems, respectively. Additionally, the performance of the proposed system is within 1 dB deviation from the Shannon limit capacity.

An enhanced iterative receiver based on vector approximate message passing for deep-sea vertical underwater acoustic communications.

Vertical underwater acoustic (UWA) communications play a crucial role in deep-sea applications. A vertical UWA channel generally features a moderate multipath but with time-varying Doppler shifts as well as loud impulsive noise. To achieve a robust vertical single-carrier UWA communication, this paper proposes an enhanced iterative receiver. First, a spline interpolation-based timing estimation approach is proposed to compensate for the time-varying Doppler effects efficiently. Then, the residual timing errors and the multipath interference are tackled by a fractionally spaced self-iterative soft equalizer (SISE) based on the vector approximate message passing (VAMP) algorithm. The VAMP-SISE consists of four parts: an inner soft slicer and an inner soft equalizer for symbol detection as well as a denoiser and a minimum mean-squared error estimator for impulsive noise suppression. Different parts iteratively exchange extrinsic information to improve the equalization performance. Last, a channel-fitting irregular convolutional code and a unity-rate code are employed at the transmitter to lower the signal-to-noise ratio threshold for reliable communications. Deep-sea experiments verify the performance superiority of the proposed receiver over existing schemes.

Cooperative Non-Orthogonal Multiple Access for Beyond 5G Networks

In the beyond 5G networks, extraordinary demands for data rates and capacity are to be met. A possible candidate to address these challenges is Non-Orthogonal Multiple Access (NOMA) technique, which leads to higher diversity gains and massive connectivity. One caveat of NOMA is the increased receiver complexity to nullify the Inter User Interference (IUI) through Successive Interference Cancellation (SIC). In this paper, a cooperative relaying scheme is employed to improve the overall diversity gain and data rates of the NOMA system. Extrinsic Information Transfer (EXIT) charts are employed to examine the cooperative NOMA system’s user fairness as well as its performance while implementing the IRregular Convolutional Code (IRCC). The EXIT chart using IRCC evaluates the convergence analysis for the proposed system. Furthermore, the implementation of EXIT charts for optimization convergence is exploited by using power optimization and the SIC for the joint rate to evaluate the fairness of the system. Simulation results shows that cooperative NOMA helps to achieve higher diversity gain and improved data rate for the cooperative NOMA system.

Performance Analysis and Improvement for VAMP Soft Frequency-Domain Equalizers

The vector approximate message passing (VAMP) soft frequency-domain equalizer (SFDE) has been proposed for turbo equalization. It consists of an inner soft equalizer (ISE) and an inner soft slicer (ISS), which iteratively exchange block-wise extrinsic information to improve the equalization performance, analogous to the outer turbo iteration between a soft equalizer and a soft decoder. However, a comparison of the VAMP-SFDE with other types of self-iterative SFDEs, including the self-iterative block-wise soft interference cancellation (SI-BSIC) SFDE and the generalized approximate message passing (GAMP) SFDE, is lacking. Moreover, comprehensive performance analysis for the VAMP-SFDE is yet to be performed. In this paper, relations among the VAMP-SFDE, the SI-BSIC-SFDE, and the GAMP-SFDE are first revealed. After that, the performance analysis is provided for the VAMP-SFDE and it leads to an improved semi-adaptive damping (SAD) scheme for maintaining the independence between the ISS and ISE. The resulting SAD-VAMP-SFDE shows improved mean square error (MSE) evolution curves compared with the original VAMP-SFDE. The SAD-VAMP-SFDE-based turbo equalization outperforms those using the SI-BSIC-SFDE or GAMP-SFDE and approaches the matched filter bound (MFB) over low signal-to-noise ratio region. To further demonstrate its superiority, the SAD-VAMP-SFDE is employed to enable a near-capacity transceiver design, which adopts the serial concatenation of an irregular convolutional code and a unity-rate code on the transmitter side.

Distributed Irregular Codes Relying on Decode-and-Forward Relays as Code Components

A near-capacity distributed coding scheme is conceived by incorporating multiple relay nodes (RNs) for constructing a virtual irregular convolutional code (IRCC). We first compute the relay channel's capacity and then design IRCCs for the source and relay nodes. Extrinsic information transfer (EXIT) charts are utilized to design the codes for approaching the achievable capacity of the relay channels. Additionally, we improve the transmit power efficiency of the overall system by invoking both power allocation and relay selection. We found that even a low-complexity repetition code or a unit-memory convolutional code is capable of forming a near-capacity virtual IRCC. The performance of the proposed distributed IRCC (DIRCC) scheme is shown to be perfectly consistent with that predicted from the EXIT chart. More specifically, the DIRCC scheme is capable of operating within 0.68 dB from the corresponding lower bound of the relay channel capacity, despite the fact that each RN is exposed to realistic decoding errors due to communicating over imperfect source–relay channels.

The Road From Classical to Quantum Codes: A Hashing Bound Approaching Design Procedure

Powerful Quantum Error Correction Codes (QECCs) are required for stabilizing and protecting fragile qubits against the undesirable effects of quantum decoherence. Similar to classical codes, hashing bound approaching QECCs may be designed by exploiting a concatenated code structure, which invokes iterative decoding. Therefore, in this paper we provide an extensive step-by-step tutorial for designing EXtrinsic Information Transfer (EXIT) chart aided concatenated quantum codes based on the underlying quantum-to-classical isomorphism. These design lessons are then exemplified in the context of our proposed Quantum Irregular Convolutional Code (QIRCC), which constitutes the outer component of a concatenated quantum code. The proposed QIRCC can be dynamically adapted to match any given inner code using EXIT charts, hence achieving a performance close to the hashing bound. It is demonstrated that our QIRCC-based optimized design is capable of operating within 0.4 dB of the noise limit.

Near-Capacity Code Design for Entanglement-Assisted Classical Communication over Quantum Depolarizing Channels

We have conceived a near-capacity code design for entanglement-assisted classical communication over the quantum depolarizing channel. The proposed system relies on efficient near-capacity classical code designs for approaching the entanglement-assisted classical capacity of a quantum depolarizing channel. It incorporates an Irregular Convolutional Code (IRCC), a Unity Rate Code (URC) and a soft-decision aided Superdense Code (SD), which is hence referred to as an IRCC-URC-SD arrangement. Furthermore, the entanglement-assisted classical capacity of an N-qubit superdense code transmitted over a depolarizing channel is invoked for benchmarking. It is demonstrated that the proposed system operates within 0.4 dB of the achievable noise limit for both 2-qubit as well as 3-qubit SD schemes. More specifically, our design exhibits a deviation of only 0.062 and 0.031 classical bits per channel use from the corresponding 2-qubit and 3-qubit capacity limits, respectively. The proposed system is also benchmarked against the classical convolutional and turbo codes.

Irregular Convolution and Unity-Rate Coded Network-Coding for Cooperative Multi-User Communications

Near-Capacity Multi-user Network-coding (NCMN) based systems operating in multiple modes and relying on an amalgamated Irregular Convolutional Code, a Unity-Rate Code and M-ary Phase-Shift Keying are proposed. We consider a multiuser network in which the users cooperatively transmit their independent information to a common base station (BS). Extrinsic Information Transfer (EXIT) charts were used for designing the proposed NCMN scheme for the sake of approaching the Discrete-input Continuous-output Memoryless Channel's (DCMC) capacity. The NCMN systems are capable of simultaneously exploiting the advantages of all the new modes we designed for our system and those of the conventional mode. The design principles presented in this contribution can be extended to a vast range of NCMN based systems using arbitrary channel coding schemes.

Maximum-Throughput Irregular Distributed Space-Time Code for Near-Capacity Cooperative Communications

This paper presents an irregular distributed space-time (Ir-DST) coding scheme designed for near-capacity cooperative communications where the system's effective throughput is also maximized with the aid of a joint source-and-relay mode design procedure. At the source node, a serially concatenated scheme comprising an IRregular Convolutional Code (IRCC), a recursive unity-rate code (URC), and a space-time block code (STBC) was designed for the sake of approaching the corresponding source-to-relay link capacity, where the IRCC was optimized with the aid of EXtrinsic Information Transfer (EXIT) charts. At the relay node, another IRCC is serially concatenated with an identical STBC. Before transmitting the relayed information, the relay's IRCC is reoptimized based on EXIT chart analysis for the sake of approaching the relay channel's capacity and to maximize the relay's coding rate, which results in a maximized effective throughput. We will demonstrate that the topology of the Ir-DST system coincides with that of a distributed turbo code (DTC). At the destination node, a novel three-stage iterative decoding scheme is constructed to achieve decoding convergence to an infinitesimally low bit-error ratio (BER). Finally, our numerical results show the proficiency of our joint source-and-relay mode design procedure, demonstrating that the proposed Ir-DST coding scheme is capable of near-capacity cooperative communications and of maximizing the effective throughput.