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Aquareoviruses (AqRVs) can infect various wild or cultured bony fishes with serious muscle and viscera haemorrhage syndrome and have caused severe economic losses worldwide. Accumulating evidences have revealed the functions of viral proteins of AqRVs in RNA transcription, virion assembly, cell attachment and/or viral replication. In addition, structural information and transcription mechanism of AqRVs have been in‐depth studied through cryo‐electron microscopy combined with three‐dimensional image reconstruction. Although far from enough, structural and functional studies of AqRVs provide substantial insights into how viral proteins coordinate the replication of AqRVs and escape the host immune response. Grass carp reovirus (GCRV) is the most pathogenic AqRV isolated from aquatic animals. The completion of GCRV lifecycle requires the participation of host proteins. So far, many host factors involved in the entry and replication of GCRV have been identified. Based on the function of viral proteins and the viral lifecycle, many vaccines and antiviral agents have been developed to prevent the replication and infection of GCRV. This review summarises the structural characteristics and the composition of core proteins of AqRVs, as well as synergistic mechanisms of structural proteins on genome transcription and virus entry of AqRVs. In addition, the review highlights our current knowledge for the infection and replication, functions of non‐structural proteins, immune escape mechanisms, as well as the vaccines and antiviral agents of AqRVs, especially for GCRV. A better understanding of structure, function and immune evasion strategies of AqRVs will offer new targets for prevention and control of AqRVs in aquaculture. [ABSTRACT FROM AUTHOR]

In fast-varying channels, an orthogonal frequencydivision multiplexing system needs to insert denser pilot symbols among transmitted symbols in tracking the variation of a channel. However, using denser pilot symbols reduces transmission throughput. In this paper, we propose a pseudopilot algorithm for data detection in fast-varying channels without increasing the pilot density. Our algorithm is based on a regressional model-based least-squares-fitting approach. Within a block of received symbols, we select some data symbols and regard them as pseudopilot symbols. The receiver considers all the possible patterns of the pseudopilots and associates each of them with a data sequence and a corresponding metric. The associated data sequence, whose metric is minimum, is selected as the detected data sequence. Our algorithm is not based on a decision-directed or decision-feedback architecture because the pseudopilots do not come from any detected symbols. The proposed algorithm needs to search all the possible patterns of the pseudopilots, and the complexity may increase with the number of pseudopilots and constellation size. To reduce the number of search, we further propose two modified approaches. The simulation results show that the performance of the proposed algorithms could approach a bit-error probability lower bound that is obtained by letting the receiver know the true values of the pseudopilots. Compared with the linear interpolation method, the proposed algorithm shows obvious improvement in fast-varying channels. The proposed modified approaches could also effectively reduce the number of search while maintaining the performance. We also give the complexity analysis of the proposed algorithm and an approach to determine the degree of the regression polynomial. Index Terms--Estimation, fading channels, orthogonal frequency-division multiplexing (OFDM), pseudopilot, signal detection.

This paper considers the problem of blind joint channel estimation and data detection for orthogonal frequency-division multiplexing (OFDM) systems in a fading environment. Employing a regression model for a time-varying channel, we convert the problem into one that finds the data sequence x whose associated least-squares (LS) channel estimate z(x) is closest to the space of some regression curves (surfaces). We apply the branch-and-bound principle to solve the nonlinear integer programming problem associated with finding the curve that fits a subchannel in the LS sense. A recursive formula for fast metric update is obtained by exploiting the intrinsic characteristic of our objective function. The impacts of reordering the data sequence and selective detection are addressed. By employing a preferred order along with a selective detection method, we greatly reduce the detector complexity while giving up little performance loss. Both the complete and the reduced-complexity algorithms can be used for blind and semiblind detections of OFDM signals in a subchannel-by-subchannel manner. To further reduce the complexity and exploit the frequency-domain channel correlation, we suggest a two-stage approach that detects a few selected positions in some subchannels first, and then, treating the detected symbols as pilots, determines the remaining symbols within a properly chosen time-frequency block by a two-dimensional model-based pilot-assisted algorithm. The proposed methods do not require the information of the channel statistics like signal-to-noise ratio or channel correlation function. Performance of differential modulations like differential quaternary phase-shift keying and STAR 16-ary quadrature amplitude modulation are provided. Both blind and semiblind schemes yield satisfactory performance. Index Terms--Estimation, fading channels, signal detection.

This paper proposes a robust pilot-assisted channel estimation method for orthogonal frequency division multiplexing (OFDM) signals in Rayleigh fading. Our estimation method is based on nonlinear regression channel models. Unlike the linear minimum mean-squared error (LMMSE) channel estimate, the method proposed does not have to know or estimate channel statistics like the channel correlation matrix and the average signal-to-noise ratio (SNR) per bit. Numerical results indicate that the performance of the proposed channel estimator is very close to the theoretical bit error propagation lower bound that is obtained by a receiver with perfect channel response information. Index Terms--Equalizers, frequency-division multiplexing, gain control.