Biological sequences, including RNAs and proteins, share similarities with natural languages, enabling the application of advanced language models to various biological tasks. However, due to its flexibility and lack of experimental data, RNA is a particularly challenging biological ``language'' compared to other biological sequences like proteins. RNA multiple sequence alignments (MSAs), which align evolutionarily related RNA sequences, can greatly enhance RNA biology modeling, as evidenced by their significant roles in structure prediction and function annotation. This raises the question of whether RNA MSAs can also benefit RNA design, which remains unexplored. This paper introduces RMSAGen, a model comprising RMSA-Encoder and RMSA-Decoder, that leverages MSAs to design functional RNA sequences. RMSA-Encoder effectively extracts MSA features, enhancing performance in functional prediction and solvent accessibility prediction tasks and supporting RMSA-Decoder in accurate RNA generation. RMSAGen can design RNA sequences that effectively bind to target RNA-binding proteins, and the design performance improves with an increasing number of sequences. In addition, the ribozymes designed with structural features by RMSAGen show strong computational metrics and exhibit biological activity during gel electrophoresis. These results highlight the effectiveness of RMSAGen, establishing it as a powerful tool and a new direction for RNA design.

The intelligent question answering system aims to provide quick and concise feedback on the questions of users. Although the performance of phrase-level and numerous attention models have been improved, the sentence components and position information are not emphasized enough. This article combines Ci-Lin and word2vec to divide all of the words in the question-answer pairs into groups according to the semantics and select one kernel word in each group. The remaining words are common words and realize the semantic mapping mechanism between kernel words and common words. With this Chinese semantic mapping mechanism, the common words in all questions and answers are replaced by the semantic kernel words to realize the normalization of the semantic representation. Meanwhile, based on the bi-directional LSTM model, this article introduces a method of the combination of semantic role labeling and positional context, dividing the sentence into multiple semantic segments according to semantic logic. The weight is given to the neighboring words in the same semantic segment and propose semantic role labeling position attention based on the bi-directional LSTM model (BLSTM-SRLP). The good performance of the BLSTM-SRLP model has been demonstrated in comparative experiments on the food safety field dataset (FS-QA).

To assist hybrid beamforming in multi-user massive Multiple Input Multiple Output (MIMO) systems at millimeter wave frequencies, we propose Auxiliary Processing Network (APN) based multi-phase channel alignment techniques. The APN, which is realized in parallel to the main beamforming network, have two implementation architectures, namely the hybrid analog-digital APN based on antenna switching as well as the fully digital APN with low-resolution Analog-to-Digital Converters (ADCs). For different APN architectures, we design various channel estimation algorithms for the channel alignment procedure and evaluate the corresponding performance.

Coordinated Multi-point (CoMP) transmission and reception is considered as a promising technique to combat inter-cell interference, enhance throughput, improve mobility, reduce handover interruption time, and also to increase spectrum efficiency. In this paper, we investigate and analyze the performance of uplink intra-site joint reception CoMP (JR-CoMP) for LTE-Advanced (LTE-A) systems. Both single user-MIMO (SU-MIMO) CoMP and multiple user-MIMO (MU-MIMO) CoMP show significant gains in terms of cell average and cell-edge throughput performances. However, the complexity of JR-CoMP is a big concern for realistic systems. In this paper, we propose a novel and low-complexity JR-CoMP scheme which combines effective antenna selection (and is denoted as JR-CoMP-AS). Compared with original JR-CoMP, the proposed JR-CoMP-AS can significantly reduce the computational complexity with acceptable performance loss. Simulation results demonstrate and validate the advantage of the proposed JR-CoMP-AS scheme.

Interference has been an important performance limiting problem for wireless networks, especially for LTE networks where frequency reuse factor is 1. Interference alignment is a promising method to mitigate interference and achieve larger degrees of freedom. With only one single antenna equipped at UE, an uplink interference alignment exploiting degrees of freedom on frequency domain was introduced. Two straightforward scheduling strategies, PF and minimum interference scheduling, were proposed and analyzed. Based on the analysis, an interference alignment based coordinated scheduling (IACS) was proposed to combine the benefits of PF scheduling and minimum interference scheduling. Simulation results verified the analysis, and showed that IACS could achieve better performance for high interference scenarios.

This paper addresses the problem that how to estimate the channel practically for the large-scale multiple antenna systems. Based on the uniform linear array, we reformulate the signal model for channel estimation into a transform-domain (TD) representation. Then the TD filtering schemes are investigated. In particular, we propose a sequence-based filtering scheme, which is asymptotically optimal in the sense of noise cancelation as the antenna number grows large. The channel estimation scheme here we proposed has much lower complexity than the traditional minimum mean square error (MMSE) estimator and does not depend on channel statistical information. Simulation results validate the effectiveness of the proposed scheme.

We investigate two different relay selection (RS) methods for precoded decode-and-forward (DF) cooperative OFDM systems: one scheme is to select the best relays for individual precoding groups (IPG-RS), and the other is to choose a single relay for the entire precoding groups (EPG-RS). We derive their diversity performances from the pairwise error probability (PEP) analysis, indicating that both schemes can achieve the full frequency and cooperative diversity with a proper choice of precoding size. Numerical results also show that IPG-RS can either reduce the decoding complexity or improve the error performance significantly as compared to existing solutions whereas EPG-RS has some performance loss as a result of less communication overhead.