Wenbo Ding

Compressive Sensing Based Channel Estimation for OFDM Systems Under Long Delay Channels

Time-domain synchronous orthogonal frequency division multiplexing (TDS-OFDM) has advantages in spectral efficiency and synchronization. However, its iterative interference cancellation algorithm will suffer from performance loss especially under severely fading channels with long delays and has difficulty supporting high-order modulations like 256 QAM, which may not accommodate the emerging ultra-high definition television service. To solve this problem, a channel estimation method for OFDM under the framework of compressive sensing (CS) is proposed in this paper. Firstly, by exploiting the signal structure of recently proposed time-frequency training OFDM scheme, the auxiliary channel information is obtained. Secondly, we propose the auxiliary information based subspace pursuit (A-SP) algorithm to utilize a very small amount of frequency-domain pilots embedded in the OFDM block for the exact channel estimation. Moreover, the obtained auxiliary channel information is adopted to reduce the complexity of the classical SP algorithm. Simulation results demonstrate that the CS-based OFDM outperforms the conventional dual pseudo noise padded OFDM and CS-based TDS-OFDM schemes in both static and mobile environments, especially when the channel length is close to or even larger than the guard interval length, where the conventional schemes fail to work completely.

Time–Frequency Joint Sparse Channel Estimation for MIMO-OFDM Systems

This letter proposes a time-frequency joint sparse channel estimation for multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems under the framework of structured compressive sensing (CS). The proposed scheme first relies on a pseudorandom preamble, which is identical for all transmit antennas, to acquire the partial common support by utilizing the sparse common support property of the MIMO channels. Then, a very small amount of frequency-domain orthogonal pilots are used for the accurate channel recovery. Simulation results show that the proposed scheme demonstrates better performance and higher spectral efficiency than the conventional MIMO-OFDM schemes. Moreover, the obtained partial common support can be further utilized to reduce the complexity of the CS algorithm and improve the signal recovery probability under low signal-to-noise-ratio conditions.

An Indoor Broadband Broadcasting System Based on PLC and VLC

Visible light communication (VLC) using the light-emitting diode (LED) will become an appealing alternative to the radio frequency communication technology for indoor wireless broadband broadcasting. However, the LED lamps should access to the backbone information network and this requirement is not easily satisfied. Power line communication (PLC) systems utilize the ubiquitous power line network to power the LED lamps while serving as the backbone network for the VLC systems naturally. In this paper, we propose a novel and cost-effective indoor broadband broadcasting system based on the deep integration of PLC and VLC. The proposed scheme significantly reduces the complexity of the VLC network protocol, and requires much less modification to the current infrastructure, while providing better signal coverage. A two-lamp network demo is implemented and the performance evaluation for the proposed scheme is carried out in the laboratory. The proposed scheme is an appealing solution for the indoor family broadcasting, and could be well extended to the scenarios including the hospitals, shopping malls, stadiums, music halls, and etc.

3D Orthogonal Woven Triboelectric Nanogenerator for Effective Biomechanical Energy Harvesting and as Self‐Powered Active Motion Sensors

The development of wearable and large-area energy-harvesting textiles has received intensive attention due to their promising applications in next-generation wearable functional electronics. However, the limited power outputs of conventional textiles have largely hindered their development. Here, in combination with the stainless steel/polyester fiber blended yarn, the polydimethylsiloxane-coated energy-harvesting yarn, and nonconductive binding yarn, a high-power-output textile triboelectric nanogenerator (TENG) with 3D orthogonal woven structure is developed for effective biomechanical energy harvesting and active motion signal tracking. Based on the advanced 3D structural design, the maximum peak power density of 3D textile can reach 263.36 mW m-2 under the tapping frequency of 3 Hz, which is several times more than that of conventional 2D textile TENGs. Besides, its collected power is capable of lighting up a warning indicator, sustainably charging a commercial capacitor, and powering a smart watch. The 3D textile TENG can also be used as a self-powered active motion sensor to constantly monitor the movement signals of human body. Furthermore, a smart dancing blanket is designed to simultaneously convert biomechanical energy and perceive body movement. This work provides a new direction for multifunctional self-powered textiles with potential applications in wearable electronics, home security, and personalized healthcare.

Shape Memory Polymers for Body Motion Energy Harvesting and Self‐Powered Mechanosensing

Growing demand in portable electronics raises a requirement to electronic devices being stretchable, deformable, and durable, for which functional polymers are ideal choices of materials. Here, the first transformable smart energy harvester and self-powered mechanosensation sensor using shape memory polymers is demonstrated. The device is based on the mechanism of a flexible triboelectric nanogenerator using the thermally triggered shape transformation of organic materials for effectively harvesting mechanical energy. This work paves a new direction for functional polymers, especially in the field of mechanosensation for potential applications in areas such as soft robotics, biomedical devices, and wearable electronics.

A hybrid power line and visible light communication system for indoor hospital applications

Graphical abstractDisplay Omitted HighlightsA hybrid broadband PLC and VLC systems with OFDM modulation is proposed.A demonstration of supporting over 48Mbps data rate within 8MHz is provided.The hybrid system is suitable for indoor hospital applications.The hybrid system is locatable, radiation-free and high-capacity. Modern hospitals are beginning to adopt E-HEALTH as efficient complements to the traditional healthcare services. To support the E-HEALTH services, a locatable, radiation-free and high-capacity communication system is urgently needed in hospitals. Power line communication (PLC) systems can use the ubiquitous power line network to power the light-emitting diode (LED) lamps while serving as the backbone network for the indoor visible light communication (VLC) systems naturally. In this article, a hybrid broadband power line and visible light communication system with orthogonal frequency division multiplexing modulation is proposed for the indoor hospital applications, which gives a brand-new solution to replace the conventional wireless communication systems in hospitals. A general-purpose system model is provided and some basic techniques to enhance system performance are also investigated. Moreover, a feasible demonstration which supports over 48Mbps data rate within a bandwidth of 8MHz is implemented in the laboratory.

Double Kill: Compressive-Sensing-Based Narrow-Band Interference and Impulsive Noise Mitigation for Vehicular Communications

Narrow-band interference (NBI) and impulsive noise (IN) are two kinds of non-Gaussian noise that have a severe impact on vehicular communications. In this paper, a novel compressive sensing (CS)-based method of simultaneous NBI and IN mitigation is proposed, which is a double kill of the two kinds of unfavorable disturbances. A CS-based time-frequency-measuring orthogonal frequency-division multiplexing (CS-TFM-OFDM) frame structure is introduced, in which the temporal repeated training sequences (TSs) are exploited by the proposed CS-based differential measuring (CS-DM) method to acquire the CS measurement vector of the NBI. With the aid of the a priori partial support, we further proposed the a priori-aided sparsity adaptive matching pursuit (PA-SAMP) to improve the accuracy and stability of NBI recovery. Meanwhile, the measurement vector of the IN is acquired from the null subcarriers in the CS-TFM-OFDM frame. After partial support of the IN is obtained, the IN is reconstructed using the proposed PA-SAMP algorithm. Hence, the two categories of non-Gaussian noise are both thoroughly eliminated, leading to the stability and robustness of vehicular communications. The proposed CS-based approach outperforms the conventional noise suppression methods in vehicular communications environments, which is validated by theoretical analysis and computer simulations.

Indoor hospital communication systems: An integrated solution based on power line and visible light communication

Modern hospitals are beginning to adopt E-HEALTH as efficient complements to the traditional healthcare services. To support the E-HEALTH services, a locatable, radiation-free and high-capacity communication system is urgently needed in hospitals. Power line communication (PLC) system can use the ubiquitous power line network to power the light-emitting diode (LED) lights while serving as the backbone network for the indoor visible light communication (VLC) systems naturally. In this paper, an integrated broadband power line and visible light communication systems with OFDM modulation is proposed for the indoor hospital applications. This gives a brand-new solution to replace the conventional wireless communication systems in hospitals.

Nonorthogonal Time–Frequency Training-Sequence-Based CSI Acquisition for MIMO Systems

In this paper, a spectrally efficient nonorthogonal time-frequency training sequence (TS)-based channel state information (CSI) acquisition approach is proposed for multiple-input-multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) systems under the framework of structured compressed sensing (SCS). The scheme first relies on a time-domain TS that is identical for all transmit antennas to acquire the partial channel common support by utilizing the spatial correlation property of the MIMO channels and then uses the frequency-domain TS for accurate CSI recovery based on the proposed adaptive spatially-temporally joint simultaneous orthogonal matching pursuit algorithm. Here, the obtained partial channel common support can be utilized to reduce the complexity of the classical SCS algorithm and improve the signal recovery probability. Simulation results show that the proposed scheme could significantly reduce the TS overhead and demonstrate better performance than the existing MIMO-OFDM systems, which might be suitable for massive MIMO systems in future fifth-generation communications.

Novel Approach to Design Time-Domain Training Sequence for Accurate Sparse Channel Estimation

Nowadays, orthogonal frequency division multiplexing system plays a more and more important role in telecommunication systems where the training sequence (TS) is usually adopted for synchronization and channel estimation, such as in the digital television/terrestrial multimedia broadcasting system. However, to achieve a channel estimation scheme with both high accuracy and spectrum efficiency is still challenging due to noise interference and delay spread of the propagation channel. In this paper, by applying the compressive sensing (CS) theory into the sparse channel estimation process for time-domain TS, a thorough investigation on the TS design criteria is carried out. Three criteria to optimize the TS design, which are to minimize the hyper-factors for coherence, the cumulative coherence, and the coherence variance, respectively, are proposed to improve the recovery performance. To minimize the corresponding merit factors of the proposed criteria, we first investigate a CS-based inverse discrete Fourier transform pattern of TS with cyclic structure, and then a genetic algorithm is proposed to further lower the merit factors. The simulation results show that by using the proposed optimized TSs, the channel estimation performance outperforms those obtained by either conventional pseudo-random noise sequence or brute force searching sequence in correct recovery probability, mean square error, and bit error rate. Moreover, the proposed criteria II and III have better performance than criterion I, while criterion III has the lowest computational complexity and is the most suitable for application.