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Abstract-In this paper we propose a progressive receiver for orthogonal-frequency-division-multiplexing (OFDM) transmission over time-varying underwater acoustic (UWA) channels. The progressive receiver is in nature an iterative receiver. However, it distinguishes itself from existing iterative receivers in that the system model itself for channel estimation and data detection keeps being updated during the iterations. When the decoding in the current iteration is not successful, the receiver increases the span of the inter-carrier interference (ICI) in the model and utilizes the available soft information from the decoder to assist the next iteration which deals with a channel with larger Doppler spread. Numerical simulation and experimental data collected from the SPACE08 experiment show that the proposed receiver can self adapt to channel variations, enjoying low complexity in calm channel conditions while maintaining excellent performance in tough channel conditions.

Abstract-Recently it has been shown that sparse channel estimation, implemented with orthogonal matching pursuit (OMP) and basis pursuit (BP) algorithms, has impressive performance gains over alternatives that do not take advantage of the channel sparsity, for underwater acoustic (UWA) communications. We in this paper compare the performance and complexity of three popular BP algorithms, namely l1 ls, SpaRSA, and YALL1, using both simulation and experimental data for underwater orthogonal frequency division multiplexing (OFDM) systems with both single and multiple transmitters. We find that all BP solvers achieve similar block-error-rate performance, considerably outperforming OMP. In terms of complexity, both SpaRSA and YALL1 reduce the runtime by about one order of magnitude relative to l1 ls, catching up with OMP. The efficient BP solvers such as SpaRSA and YALL1 are thus appealing to be implemented in real-time underwater OFDM modems.

We propose a block-by-block iterative receiver for underwater MIMO-OFDM that couples channel estimation with multiple-input multiple-output (MIMO) detection and low-density parity-check (LDPC) channel decoding. In particular, the channel estimator is based on a compressive sensing technique to exploit the channel sparsity, the MIMO detector consists of a hybrid use of successive interference cancellation and soft minimum mean-square error (MMSE) equalization, and channel coding uses nonbinary LDPC codes. Various feedback strategies from the channel decoder to the channel estimator are studied, including full feedback of hard or soft symbol decisions, as well as their threshold-controlled versions. We study the receiver performance using numerical simulation and experimental data collected from the RACE08 and SPACE08 experiments. We find that iterative receiver processing including sparse channel estimation leads to impressive performance gains. These gains are more pronounced when the number of available pilots to estimate the channel is decreased, for example, when a fixed number of pilots is split between an increasing number of parallel data streams in MIMO transmission. For the various feedback strategies for iterative channel estimation, we observe that soft decision feedback slightly outperforms hard decision feedback.

Background Adipose tissue plays a central role in obesity-related metabolic diseases such as type 2 diabetes. Salvianolic acid B (Sal B), a water-soluble ingredient derived from Salvia miltiorrhiza, has been shown to reduce obesity and obesity-related metabolic diseases by suppressing adipogenesis. However, the role of Sal B in white adipose tissue (WAT) is not yet clear. Methods Illumina Hiseq 4000 was used to study the effects of Sal B on the expression of long non-coding RNA (lncRNA) and circular RNA (circRNA) in epididymal white adipose tissue induced by a high fat diet in obese mice. Results RNA-Seq data showed that 234 lncRNAs, 19 circRNAs, and 132 mRNAs were differentially expressed in WAT under Sal B treatment. The up-regulated protein-coding genes in WAT of the Sal B-treated group were involved in the insulin resistance pathway, while the down-regulated genes mainly participated in the IL-17 signaling pathway. Other pathways may play an important role in the formation and differentiation of adipose tissue, such as B cell receptor signaling. Analysis of the lncRNA–mRNA network provides potential targets for lncRNAs in energy metabolism. We speculate that Sal B may serve as a potential therapeutic approach for obesity.