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In this paper, we propose a transmission control scheme for the approximate message passing (AMP)-based joint user identification and channel estimation in massive connectivity networks. In the proposed transmission control scheme, a transmission control function is designed to determine a user’s transmission probability, when it has a transmission demand. By employing a step transmission control function for the proposed scheme, we derive the channel distribution experienced by the receiver to describe the effect of transmission control on the design of AMP algorithm. Based on that, we modify the AMP algorithm by designing a minimum mean squared error (MMSE) denoiser, to jointly identify the user activity and estimate their channels. We further derive the false alarm and missed detection probabilities to characterize the user identification performance of the proposed scheme. Closed-form expressions of the average packet delay and the network throughput are obtained. Furthermore, we optimize the transmission control function to maximize the network throughput. We demonstrate that the proposed scheme can significantly improve the user identification and channel estimation performance, reduce the average delay, and boost the throughput, compared to the conventional scheme without transmission control. [ABSTRACT FROM AUTHOR]

We propose a new class of partially information-coupled (PIC) turbo codes to improve the transport block (TB) error rate performance for long-term evolution (LTE) systems, while keeping the hybrid automatic repeat request protocol and the turbo decoder for each code block (CB) unchanged. In the proposed codes, every two consecutive CBs in a TB are coupled together by sharing partial information bits. This coding structure introduces irregular variable node degree distributions in the Tanner graph of the PIC-turbo codes. We propose a feedforward and feedback decoding scheme and a windowed decoding scheme to decode the whole TB by exploiting the coupled information between CBs. We calculate the extrinsic information transfer (EXIT) functions for the PIC-turbo codes by assuming that the coupled information are perfectly decoded. An SNR gain upper bound of the PIC-turbo codes over the LTE turbo codes for various coupling ratios is derived by the calculated EXIT charts. Numerical results show that the proposed codes achieve an SNR gain of 0.26–0.73 dB for various code parameters at a TB error rate level of $10^{-2}$ , which complies with the derived SNR gain upper bound. [ABSTRACT FROM AUTHOR]

We propose chained low-density parity-check codes to improve the transport block (TB) error rate performance for high-throughput future communications. The proposed codes connect multiple code blocks (CBs) in a TB into a chain by coupling a few information bits between every two consecutive CBs and insert dummy bits at two ends of the chain. We propose a feed-forward and feed-back TB decoding scheme. We employ the protograph extrinsic information transfer analysis to optimize the coupling pattern to minimize the decoding threshold of the proposed codes. Numerical results demonstrate the excellent TB error rate performance of the proposed codes. [ABSTRACT FROM PUBLISHER]

We propose an algorithm to construct a group of rate-compatible tail-biting convolutional codes (RC-TBCCs) with consistently good frame error rate performance for both short and long information lengths. The algorithm considers the free distance property and the minimum distance profile of a TBCC jointly. We construct a group of RC-TBCCs with code rates $1/n$ , $3\leq n\leq 12$ . Numerical results show that the constructed RC-TBCCs have better frame error rate performance than the TBCCs used in LTE standards for various information lengths and code rates. [ABSTRACT FROM PUBLISHER]