In Passive coherent location (PCL) radar using FM signal as emitter of opportunity the multipath propagation from transmitter to the reference antenna strongly decreases the radar detection ability. Thus, multipath re...
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ISBN:
(纸本)9780819491718
In Passive coherent location (PCL) radar using FM signal as emitter of opportunity the multipath propagation from transmitter to the reference antenna strongly decreases the radar detection ability. Thus, multipath removal from reference signal is a very important stage of signal processing in radar system. Since the FM signal with constant envelope is used the commonly known constant modulus algorithms suit very well for this purpose. In this introductory paper, we propose to use a block least squares constant modulus algorithm which has better convergence properties then the conventional LMS-type algorithm presented in literature. It appears as very appealing alternative since in further applications (not presented in this paper) it will very likely enable to achieve satisfactory results with less amount of data (signal samples).
In order to improve the ability of normal mode blind equalizer to deal with inter-code crosstalk,a blind equalization algorithm based on brainstorming algorithm is *** algorithm starts with the problem of unsatisfacto...
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In order to improve the ability of normal mode blind equalizer to deal with inter-code crosstalk,a blind equalization algorithm based on brainstorming algorithm is *** algorithm starts with the problem of unsatisfactory initialization of the equalizer,and uses the brainstorming algorithm to quickly and accurately find the advantages of the global solution,reducing the initial mean square error of the system;on this basis,from the perspective of the convergence speed and convergence stability of the weighing instrument,the adaptive ability of the variable step error function is used to improve the equalization effect of the *** results show that the new equalization algorithm can reduce the initial mean square error,accelerate the convergence speed of the equalizer,and improve the communication performance of the system.
This article presents the decision feedback equalizer (DFE), the maximum likelihood detection (MLD), and the radius-directed equalization (RDE) algorithms designed in MATLAB-R2018a to equalize the received signal in a...
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This article presents the decision feedback equalizer (DFE), the maximum likelihood detection (MLD), and the radius-directed equalization (RDE) algorithms designed in MATLAB-R2018a to equalize the received signal in a dispersive optical link up to 120 km. DFE is essential for improving signal quality in several communication systems, including WiFi networks, cable modems, and long-term evolution (LTE) systems. Its capacity to mitigate inter-symbol interference (ISI) and rapidly adjust to channel variations renders it a flexible option for high-speed data transfer and wireless communications. Conversely, MLD is utilized in applications that require great precision and dependability, including multi-input-multi-output (MIMO) systems, satellite communications, and radar technology. The ability of MLD to optimize the probability of accurate symbol detection in complex, high-dimensional environments renders it crucial for systems where signal integrity and precision are critical. Lastly, RDE is implemented as an alternative algorithm to the CMA-based equalizer, utilizing the idea of adjusting the amplitude of the received distorted symbol so that its modulus is closer to the ideal value for that symbol. The algorithms are tested using a converged 5G mm-wave analog radio-over-fiber (A-RoF) system at 60 GHz. Their performance is measured regarding error vector magnitude (EVM) values before and after equalization for different optical fiber lengths and modulation formats (QPSK, 16-QAM, 64-QAM, and 128-QAM) and shows a clear performance improvement of the output signal. Moreover, the performance of the proposed algorithms is compared to three commonly used algorithms: the simple least mean square (LMS) algorithm, the constant modulus algorithm (CMA), and the adaptive median filtering (AMF), demonstrating superior results in both QPSK and 16-QAM and extending the transmission distance up to 120 km. DFE has a significant advantage over LMS and AMF in reducing the inter-symbol
This paper improves our previously proposed semi-blind uplink interference suppression scheme for multicell multiuser massive MIMO systems by incorporating the beamspace approach. The constant modulus algorithm (CMA),...
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This paper improves our previously proposed semi-blind uplink interference suppression scheme for multicell multiuser massive MIMO systems by incorporating the beamspace approach. The constant modulus algorithm (CMA), a known blind adaptive array scheme, can fully exploit the degree of freedom (DoF) offered by massive antenna arrays to suppress inter-user interference (IUI) and inter-cell interference (ICI). Unfortunately, CMA wastes a lot of the benefit of DoF for null-steering even when the number of incoming signal is fewer than that of receiving antenna elements. Our new proposal introduces the beamspace method which degenerates the number of array input for CMA from element-space to beamspace. It can control DoF expended for subsequent interference suppression by CMA. Optimizing the array beamforming gain and null-steering ability, can further improve the output signal-to-interference and noise power ratio (SINR). Computer simulation confirmed that our new proposal reduced the required number of data symbols by 34.6%. In addition, the 5th percentile SINR was also improved by 14.3 dB.
The finite length absolute minimum vectors of the constantmodulus (CM) criterion with an arbitrary source and a single output linear regression model are shown to equal the Wiener filter or one of its phase shifted v...
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The finite length absolute minimum vectors of the constantmodulus (CM) criterion with an arbitrary source and a single output linear regression model are shown to equal the Wiener filter or one of its phase shifted versions. The exact equations for these vectors are also provided and depend on the second and the fourth order statistical moments of the sample sequence only. These expressions describe the behavior of the constant modulus algorithm (CMA) when it operates at the desired global minimum and expose key characteristics of the CM minimization approach. These characteristics include the existence conditions, the persistency of excitation, the computational complexity, the excess CM cost, the robustness to an additive noise, and the tolerance to the length variations. Moreover, several computer simulation experiments are included to validate our findings. (C) 2018 Published by Elsevier Inc.
To improve the performance of the blind equalizer (BE) in impulsive noise environments, a robust maximum likelihood algorithm (RMLA) is proposed for the communication systems using quadrature amplitude modulation sign...
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To improve the performance of the blind equalizer (BE) in impulsive noise environments, a robust maximum likelihood algorithm (RMLA) is proposed for the communication systems using quadrature amplitude modulation signals. A novel robust maximum likelihood cost function based on the constant modulus algorithm is constructed to effectively suppress the influence of impulsive noise and ensure the computational stability. Theoretical analysis is presented to illustrate the robustness and good computational stability of the proposed algorithm under the impulsive noise ambient. Moreover, it is proved that the weight vector of the proposed BE can converge stably by LaSalle invariance principle. Simulation results are provided to further confirm the robustness and stability of the proposed RMLA.
We present novel convex-optimization-based solutions to the problem of blind beamforming of constantmodulus signals, and to the related problem of linearly constrained blind beamforming of constantmodulus signals. T...
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ISBN:
(纸本)9781538615713
We present novel convex-optimization-based solutions to the problem of blind beamforming of constantmodulus signals, and to the related problem of linearly constrained blind beamforming of constantmodulus signals. These solutions are based on a low-rank approximation, ensure global optimality and are parameter free, namely, do not contain any tuneable parameters and do not require any a-priori parameter settings. The proposed approach outperforms state-of-the-art both in terms of the number of required samples for convergence, and in terms of the beamformer output SINR.
In order to overcome the inter-symbol interference generated by multipath effect and improve the frequency band utilization ratio in the underwater acoustic communication system, the blind equalization problem of the ...
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ISBN:
(纸本)9781728118598
In order to overcome the inter-symbol interference generated by multipath effect and improve the frequency band utilization ratio in the underwater acoustic communication system, the blind equalization problem of the underwater acoustic channel is expressed as the support vector regression problem. The error function of constant modulus algorithm (CMA) and multi-modulusalgorithm (MMA) are included in the penalty term of the SVR, and the iterative reweighted least squares (IRWLS) method is used to find the optimal equalizer coefficients, thus two batch blind equalization algorithms are proposed in this paper. The simulation experiments show that the proposed two batch algorithms can effectively realize the blind equalization of underwater acoustic channel, compared with the traditional online blind algorithm, they achieves fast convergence with small samples and have excellent blind equalization performance.
This paper addresses the problem of blind demixing of instantaneous mixtures in a multiple-input multiple-output communication system. The main objective is to present efficient blind source separation (BSS) algorithm...
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This paper addresses the problem of blind demixing of instantaneous mixtures in a multiple-input multiple-output communication system. The main objective is to present efficient blind source separation (BSS) algorithms dedicated to moderate or high-order quadratic-amplitude modulation (QAM) constellations. Four new iterative batch, BSS algorithms are presented dealing with the multimodulus (MM) and alphabet matched (AM) criteria. For the optimization of these cost functions, iterative methods of Givens and hyperbolic rotations are used. A prewhitening operation is also utilized to reduce the complexity of design problem. It is noticed that the designed algorithms using Givens rotations give satisfactory performance only for a large number of samples. However, for a small number of samples, the algorithms designed by combining both Givens and hyperbolic rotations compensate for the ill-whitening that occurs in this case and thus improves the performance. Two algorithms dealing with the MM criterion are presented for moderate-order QAM signals such as 16-QAM. The other two dealing with the AM criterion are presented for high-order QAM signals. These methods are finally compared with the state-of-the-art batch BSS algorithms in terms of signal-to-interference and noise ratio, symbol error rate, and convergence rate. Simulation results show that the proposed methods outperform the contemporary batch BSS algorithms.
Massive multiple-input multiple-output (MIMO) transmission, in which the number of antennas is considerably more than the number of user terminals, has attracted attention as a key technology in next-generation mobile...
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Massive multiple-input multiple-output (MIMO) transmission, in which the number of antennas is considerably more than the number of user terminals, has attracted attention as a key technology in next-generation mobile communication systems, because it enables improvements in the service area and interference mitigation with simple signal processing. Multi-beam massive MIMO employing high-power beam selection in the analog part and a blind algorithm in the digital part, such as the constant modulus algorithm that does not need channel state information, has been proposed and shown to offer high transmission efficiency. In this paper, in order to realize higher transmission rates and communication efficiency, we propose a beam-selection method that uses multi-beam amplitude information only. Furthermore, this method can be realized through signal processing with a simple configuration and is highly suitable for hybrid analog-digital massive MIMO, which is advantageous in terms of cost and power consumption. Here, the effectiveness of the proposed method is verified by computer simulation.
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