In TD-LTE test verification system, a proper method is needed for the parameters' transfer, which is based on software and hardware co-simulation platform. In this paper, the hybrid Real-Time communication network...
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ISBN:
(纸本)9781467395885
In TD-LTE test verification system, a proper method is needed for the parameters' transfer, which is based on software and hardware co-simulation platform. In this paper, the hybrid Real-Time communication network, which is composed of TCP/IP protocol, UDP protocol and reflective memory technology on account of hardware board, was built and a loopback test system between system simulation and link system for parameters' interface has been formed. The entire system has realized the sending and receiving of the parameters, which is fast, scalable and flexible link by either the optical fibers or LAN cable. Results show that the latency of the data could prove the key microsecond-level delay. That not only ensures the complex Real-Time of communication system, but also does not lose the parameters' information of the whole system.
Considering the limitation of hardware requirement and power dissipation in wearable brain-computer interface (BCI), the electroencephalogram (EEG) data compression implemented by independent component analysis (ICA) ...
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Considering the limitation of hardware requirement and power dissipation in wearable brain-computer interface (BCI), the electroencephalogram (EEG) data compression implemented by independent component analysis (ICA) combined with compressed sensing (CS) is proposed in this paper. A simple and effective ICA spatial filtering method is used to obtain motor related independent components (MRICs). Furthermore, CS algorithm is introduced to compress MRICs, which have advantage of frequency sparse. So the proposed scheme can make few MRICs compressed transmission instead of the multi-channel EEG data transmission. Based on the measured motor imagery EEG data, the proposed EEG compression scheme is compared with the traditional CS compression scheme. The experimental results show that, the two system schemes have the similar classification accuracy. However, in the proposed compression scheme, the amount of transmission data can be reduced by 75%.
In massive multiple-input multiple-output (MIMO) system, scaling up the antennas of base station (BS) has a clear benefit on sum rate and energy efficiency, but the signalprocessing complexity can be very high and ma...
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In massive multiple-input multiple-output (MIMO) system, scaling up the antennas of base station (BS) has a clear benefit on sum rate and energy efficiency, but the signalprocessing complexity can be very high and many algorithms cannot be implemented in practice for high hardware cost. Approximative Matrix Inverse Computations (AMIC) algorithm is a kind of low-complexity precoding for large multiuser MIMO systems, but the Bite Error Rate (BER) performance is shown to be not better than the classical MMSE precoding. To improve the BER performance of AMIC algorithm, in this paper, we use norm minimization algorithm to change the coefficient of the precoding matrix to improve the BER performance of AMIC algorithm. It can verify that the proposed algorithm can achieve better BER performance than the AMIC algorithm by using only a limited number of Neumann series iterations, and keep lower complexity. The proposed scheme is a compromise solution between complexity and BER performance.
In order to resolves the problem of occlusion in process of target tracking, an improved anti-occlusion tracking algorithm was proposed in this paper based on compressive particle filtering (CPF). Compressive sensing ...
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ISBN:
(纸本)9781467395885
In order to resolves the problem of occlusion in process of target tracking, an improved anti-occlusion tracking algorithm was proposed in this paper based on compressive particle filtering (CPF). Compressive sensing theory was introduced into particle filter (PF) framework to ensure the instantaneity of tracking. We apply the histogram with spatial information and sub-part matching ideas in the compressive particle filtering algorithm to enhance the robustness of tracking when the target was blocked by barriers. In this approach, we adopt different strategies to tracking target when the target was occluded or not. When the target was occluded, tracking it by compressive particle filtering algorithm based on sub-part matching and updating the target templates to fits the change of target appearance, otherwise, tracking it by the general compressive particle filtering algorithm. This approach bring about better robustness and tracking speed compared with the particle filtering algorithm and compressive tracking algorithm.
This paper proposes a novel reversible data-hiding scheme utilizing two steganographic images. The proposed method is able to hide more secret messages than other messages by studying the characters of embedded messag...
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This paper proposes a novel reversible data-hiding scheme utilizing two steganographic images. The proposed method is able to hide more secret messages than other messages by studying the characters of embedded messages. We transformed the form of the secret message byte from 8 binary bits to 7-base digits, which was departed to 3-digit planes to allow for hiding more secret messages through use of an extensional key matrix M*. The horizontal and vertical coordinate of the key matrix M* ranges are from 0 to 255. Therefore, we use the pixel pairs in a cover image to help hide secret message bytes in the method proposed. In key matrix M*, a point can be located by a horizontal coordinate and a vertical coordinate, which are the exact paired pixels. After embedding data by using the coordinates in the key matrix and then obtaining two stego images, we can recover the cover image after extracting the embedded data. Experiments show that the method proposed can hide more pixels in an image and recover the image accurately with only a tiny decrease in image quality.
Since the existing full-rate cooperative transmission schemes have a serious defect in low Bit Error Rate (BER) performance while the existing high-rate cooperative transmission schemes have a serious defect in low sp...
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Since the existing full-rate cooperative transmission schemes have a serious defect in low Bit Error Rate (BER) performance while the existing high-rate cooperative transmission schemes have a serious defect in low spectral efficiency, a distributed high-rate cooperative relay transmission scheme based on full-rate cooperative communication model is proposed in this paper, in which Cyclic Delay Diversity (CDD) technology and Linear Constellation Precoding (LCP) technology are employed. Moreover, the proposed scheme addresses the issue of obtaining maximum spatial and multipath diversity with low decoding complexity and high transmission reliability. The BER performance of the proposed scheme is contrasted to that of the full-rate transmission scheme where better performance is achieved, and is improved when the number of the multipath or the relay nodes increases.
Since the single-antenna relay cooperative communication systems have a serious defect in reliability of data transmission, while the MIMO communication systems have difficulty in design and decoding, we propose a mix...
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Since the single-antenna relay cooperative communication systems have a serious defect in reliability of data transmission, while the MIMO communication systems have difficulty in design and decoding, we propose a mixed structure of full-rate and low-detection complexity cooperative relay transmission scheme based on full-rate relay cooperative transmission model, which combines the advantages of cyclic delay diversity (CDD) technology and linear constellation precoding (LCP) technology. This scheme can excavation diversity gain by using single antenna terminal and multiple antenna simultaneously, moreover, the decoding complexity is low. The bit error rate (BER) performance is improved with the number of the antenna or the multipath or the relay nodes increases.
In massive multiple-input multiple-output(MIMO) system, scaling up the antennas of base station(BS) has a clear benefit on sum rate and energy efficiency, but the signalprocessing complexity can be very high and ...
详细信息
In massive multiple-input multiple-output(MIMO) system, scaling up the antennas of base station(BS) has a clear benefit on sum rate and energy efficiency, but the signalprocessing complexity can be very high and many algorithms cannot be implemented in practice for high hardware cost. Approximati ve Matrix Inverse Computations(AMIC) algorithm is a kind of lowcomplexity precoding for large multiuser MIMO systems, but the Bite Error Rate(BER) performance is shown to be not better than the classical MMSE precoding. To improve the BER performance of AMIC algorithm, in this paper, we use norm minimization algorithm to change the coefficient of the precoding matrix to improve the BER performance of AMIC algorithm. It can verify that the proposed algorithm can achieve better BER performance than the AMIC algorithm by using only a limited number of Neumann series iterations, and keep lower complexity. The proposed scheme is a compromise solution between complexity and BER performance.
IEEE 802.11 is a protocol standard widely used in wireless local area network (WLAN). For the distributed coordination function (DCF) of IEEE 802.11 MAC layer, the binary exponential backoff (BEB) algorithm has the de...
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IEEE 802.11 is a protocol standard widely used in wireless local area network (WLAN). For the distributed coordination function (DCF) of IEEE 802.11 MAC layer, the binary exponential backoff (BEB) algorithm has the defect of poor access fairness. To address this issue, the design criteria of backoff algorithm is generalized from the analysis of the key performance parameters of DCF, and then a logarithmic backoff (LB) algorithm based on dynamic contention window (CW) adjustment is proposed. The algorithm dynamically adjusts the initial value of CW and the backoff size of the CW by using the logarithmic function that takes the number of network competing nodes as the variable. Simulation results show that compared with the BEB algorithm, the LB algorithm can effectively improve the fairness performance and the throughput performance, and also reduce network delay.
A discrete observer-based repetitive control(RC) design method for a linear system with uncertainties was presented based on two-dimensional(2D) system theory. Firstly, a 2D discrete model was established to describe ...
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A discrete observer-based repetitive control(RC) design method for a linear system with uncertainties was presented based on two-dimensional(2D) system theory. Firstly, a 2D discrete model was established to describe both the control behavior within a repetition period and the learning process taking place between periods. Next, by converting the designing problem of repetitive controller into one of the feedback gains of reconstructed variables, the stable condition was obtained through linear matrix inequality(LMI) and also the gain coefficient of repetitive system. Numerical simulation shows an exceptional feasibility of this proposal with remarkable robustness and tracking speed.
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