Wenqian Wu

Bio: Wenqian Wu is an academic researcher from Southeast University. The author has contributed to research in topics: Communication channel & MIMO. The author has an hindex of 1, co-authored 2 publications receiving 3 citations.

Shallow Underwater Acoustic Massive MIMO Communications

Abstract: The potential benefits of massive multiple-input multiple-output (MIMO) make it possible to achieve high-quality underwater acoustic (UWA) communications. Nevertheless, due to the wideband nature of UWA channels, existing massive MIMO techniques for radio frequency cannot be directly applied to UWA communications. This paper investigates a UWA massive MIMO system in the shallow-water environment, deploying large array apertures at both the transmitter and the receiver. We propose a beam-based UWA massive MIMO channel model and analyze its properties. Based on this model, we reveal that the transmit design for rate maximization can be performed in a dimension-reduced space related to the channel taps. Then, we prove that the beam-domain transmission is optimal to maximize the rate when with unlimited numbers of transducers. Furthermore, if the number of hydrophones also tends to infinity, the optimal power allocation can be obtained just by the water-filling algorithm and the corresponding rate positively correlates with the number of channel taps for the high signal-to-noise-ratio regime. Moreover, we devise a low-complexity algorithm to optimize the input covariance matrix for general cases. Simulation results illustrate the significant performance of the proposed algorithm and the high throughput achieved by massive MIMO.

Large-scale MIMO underwater acoustic communication method and system

Abstract: The invention provides a large-scale multiple-input multiple-output (MIMO) underwater acoustic communication method and a large-scale MIMO underwater acoustic communication system. A transmitting endor a receiving end is provided with a large-scale transducer array, and the transmitting end carries out the low-complexity precoding matrix design through the statistical channel information of a beam domain and the sparse characteristics of an underwater acoustic channel, wherein the low-dimension precoding design based on deterministic equivalence is suitable for the situation that the transmitting end or the receiving end is provided with the large-scale array. Particularly, when the transmitting end is configured with dozens of transmitting transducers, a precoding matrix can be obtainedthrough beam domain power distribution. And when both the transmitting end and the receiving end are provided with dozens of transducers, the optimal beam domain power distribution can be realized through a classical water injection algorithm. According to the method provided by the invention, the spectral efficiency and the power efficiency of underwater acoustic communication can be remarkably improved, so that the transmission rate and the transmission distance are greatly improved, and meanwhile, the problem that the related precoding design is complex is solved.

On the Road to 6G: Visions, Requirements, Key Technologies, and Testbeds

Abstract: Fifth generation (5G) mobile communication systems have entered the stage of commercial deployment, providing users with new services, improved user experiences as well as a host of novel opportunities to various industries. However, 5G still faces many challenges. To address these challenges, international industrial, academic, and standards organizations have commenced research on sixth generation (6G) wireless communication systems. A series of white papers and survey papers have been published, which aim to define 6G in terms of requirements, application scenarios, key technologies, etc. Although ITU-R has been working on the 6G vision and it is expected to reach a consensus on what 6G will be by mid-2023, the related global discussions are still wide open and the existing literature has identified numerous open issues. This paper first provides a comprehensive portrayal of the 6G vision, technical requirements, and application scenarios, covering the current common understanding of 6G. Then, a critical appraisal of the 6G network architecture and key technologies is presented. Furthermore, existing testbeds and advanced 6G verification platforms are detailed for the first time. In addition, future research directions and open challenges are identified to stimulate the on-going global debate. Finally, lessons learned to date concerning 6G networks are discussed.

Pilot Assisted MIMO-OFDM-IM Design for Time-Varying Underwater Acoustic Communications

Abstract: This paper proposes a multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing-index modulation (OFDM-IM) design for underwater acoustic communications. The proposed MIMO-OFDM-IM utilizes an equally spaced known data (pilot subcarriers). This feature assists in overcoming different dilemmas that arise in underwater acoustic time-varying channels. In addition, the pilot subcarriers of the proposed communication scheme assists in channel estimation. This feature improves the overall performance of the maximum likelihood detector in the active subcarriers detection. The performance of the proposed transceiver scheme is presented using synthetic underwater acoustic channels. The proposed approach shows enhancement in the symbol error rate and outperforms the conventional MIMO-OFDM approach.

Research on Co-Channel Interference Cancellation for Underwater Acoustic MIMO Communications

Abstract: Multiple-input–multiple-output (MIMO) communication systems utilize multiple transmitters to send different pieces of information in parallel. This offers a promising way to communicate at a high data rate over bandwidth-limited underwater acoustic channels. However, underwater acoustic MIMO communication not only suffers from serious inter-symbol interference, but also critical co-channel interference (CoI), both of which degrade the communication performance. In this paper, we propose a new framework for underwater acoustic MIMO communications. The proposed framework consists of a CoI-cancellation-based channel estimation method and channel-estimation-based decision feedback equalizer (CE-DFE) with CoI cancellation functionalities for underwater acoustic MIMO communication. We introduce a new channel estimation model that projects the received signal to a specific subspace where the interference is free; therefore, the CoI is cancelled. We also introduce a CE-DFE with CoI cancellation by appending some filters from traditional CE-DFE. In addition, the traditional direct adaptive decision feedback equalization (DA-DFE) method and the proposed method are compared in terms of communication performance and computational complexity. Finally, the sea trial experiment demonstrates the effectiveness and merits of the proposed method. The proposed method achieves a more than 1 dB of output SNR over traditional DA-DFE, and is less sensitive to parameters. The proposed method provides a new approach to the design of robust underwater acoustic MODEM.

Variance State Propagation for Channel Estimation in Underwater Acoustic Massive MIMO-OFDM with Clustered Channel Sparsity

Abstract: In this paper, we investigate the channel estimation problem in underwater acoustic (UWA) massive multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. We first present a parametric UWA massive MIMO-OFDM channel model, and then formulate the channel estimation task as a sparse signal recovery problem. By exploiting the structured sparsity in the delay-Doppler-angle domain of the time-varying massive MIMO-OFDM channel, we develop a message-passing based channel estimation algorithm under the variance state propagation (VSP) framework. Simulation results show that our approach attains a significant performance improvement over the existing methods.

Adaptive Diversity Algorithm Based on Block STBC for Massive MIMO Link Misalignment in UWOC Systems

Abstract: In the past few years, underwater wireless optical communication (UWOC) has become a promising wireless communication technology in the underwater environment. Aiming at the problem formulation of sub-channel correlation enhancement occurring due to the joint impact of underwater link misalignment and turbulence in the process of optical signal transmission in an underwater optical massive multiple-input multiple-output (MIMO) system, we propose an adaptive diversity approach depending on partition space time block code (STBC). STBC technology is used to reduce the random fading of optical signals caused by turbulence. At the same time, the channel correlation occurring due to channel misalignment is effectively alleviated by adaptive processing. The adaptive diversity algorithm based on segmented STBC effectively improves the reliability and decrease complexity of underwater optical Massive MIMO communication systems. It determines the particular link misalignment degree by the channel gain matrix obtained from the channel estimation and selects different combinations of detectors according to the degree of misalignment to obtain the maximum gain of the received signal combination. Compared with the chunking scheme, simulation and result shows that the adaptive diversity algorithm improves the tolerance of the system to the link misalignment error from 30 mm to 60 mm under the same condition number of channel gain matrix, and it can still demodulate the source signal directly without requiring detection algorithm in case of a large error in the link misalignment.