In orthogonal frequency-division multiplex access (OFDMA) uplink, it is admitted that the carrier-frequency offsets (CFOs) between multi-transmitter and receiver introduce intercarrier interference (ICI) and cause sev...
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ISBN:
(纸本)0780391527
In orthogonal frequency-division multiplex access (OFDMA) uplink, it is admitted that the carrier-frequency offsets (CFOs) between multi-transmitter and receiver introduce intercarrier interference (ICI) and cause severe performance loss. In this paper, with reference to a detailed analysis of the ICI caused by CFOs, we propose a novel low-complexity iterative ICI cancellation algorithm, which is based on the perfect estimation of each user's CFO. Moreover, the convergence behaviors of the iterations are studied with three theorems, and the user-interleaving patterns suitable for this algorithm are presented. In accordance with the simulation results, we come to the conclusion that the low-complexity iterative algorithm can effectively suppress and cancel the ICI due to CFOs.
Two explicit iterative algorithms are developed in this paper for solving continuous coupled Lyapunov matrix equations. By introducing a tunable parameter, the considered matrix equations are transformed into the Kalm...
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ISBN:
(纸本)9781538629185
Two explicit iterative algorithms are developed in this paper for solving continuous coupled Lyapunov matrix equations. By introducing a tunable parameter, the considered matrix equations are transformed into the Kalman-Yakubovich matrix equations. Further, based on the obtained equations, an explicit iterative algorithm is constructed to solve the coupled Lyapunov matrix equations. In addition, by using the latest estimation an improved iterative algorithm is proposed. Some convergence results are obtained for the presented improved iterative algorithm. It is shown that the convergence performance of the proposed algorithms can be significantly improved if the tunable parameter can be properly chosen. Finally, a numerical example is given to show the merit of the presented algorithms.
Crosstalk is the major limiting issue in VDSL2 system. Based on matrix splitting and iterative theory, a general form of iterative crosstalk cancellation algorithm is first proposed for VDSL2 upstream transmission. Fr...
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ISBN:
(纸本)9781424448562
Crosstalk is the major limiting issue in VDSL2 system. Based on matrix splitting and iterative theory, a general form of iterative crosstalk cancellation algorithm is first proposed for VDSL2 upstream transmission. From using diagonal dominant and column wise diagonal dominant of crosstalk channel matrix property, two special iterative algorithms are then derived. Computer simulation results based on measured data verify that the iterative crosstalk cancellation algorithms can improve the performance and approach zero-forcing algorithm by successive iterations.
We present a local as well as a semilocal convergence analysis for some iterative algorithms in order to approximate a locally unique solution of a nonlinear equation in a Banach space setting. In the application part...
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The paper is devoted to the development of a methodology for evaluating the scalability of compute-intensive iterative algorithms used in simulating complex physical processes on supercomputer systems. The proposed me...
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ISBN:
(纸本)9781538673867
The paper is devoted to the development of a methodology for evaluating the scalability of compute-intensive iterative algorithms used in simulating complex physical processes on supercomputer systems. The proposed methodology is based on the BSF (Bulk Synchronous Farm) parallel computation model, which makes it possible to predict the upper scalability bound of an iterative algorithm in early phases of its design. The BSF model assumes the representation of the algorithm in the form of operations on lists using high-order functions. Two classes of representations are considered: BSF-M (Map BSF) and BSF-MR (Map-Reduce BSF). The proposed methodology is described by the example of the solution of the system of linear equations by the Jacobi method. For the Jacobi method, two iterative algorithms are constructed: Jacobi-M based on the BSF-M representation and Jacobi-MR based on the BSF-MR representation. Analytical estimations of the speedup, parallel efficiency and upper scalability bound are constructed for these algorithms using the BSF cost metrics on multiprocessor computing systems with distributed memory. An information about the implementation of these algorithms in C++ language using the BSF program skeleton and MPI parallel programming library are given. The results of large-scale computational experiments, performed on a cluster computing system, are demonstrated. Based on the experimental results, an analysis of the adequacy of estimations, obtained analytically by using the cost metrics of the BSF model, is made.
In this paper, we design an iterative channel estimation and data detection algorithm in delay-Doppler domain for orthogonal time frequency space (OTFS) system by taking advantage of the sparse nature of the channel i...
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ISBN:
(纸本)9781665405409
In this paper, we design an iterative channel estimation and data detection algorithm in delay-Doppler domain for orthogonal time frequency space (OTFS) system by taking advantage of the sparse nature of the channel in this domain. The proposed algorithm iterates between message-passing-aided data detection and data-aided channel estimation. This sparse channel estimation is reformulated as a specific marginalization of maximum a posteriori (MAP) problem. To deal with the intractability of this problem, we provide a Bayesian approach based on the variational mean-field approximation via the variational Bayesian expectation maximization (VB-EM) algorithm. Finally, we compare the complexity and performance in term of Bit Error Rate (BER) and Normalized Mean Square Error (NMSE) of the proposed solution to a reference solution in the literature (SP-I).
It has been shown that approximate message passing algorithm is effective in reconstruction problems for compressed sensing. To evaluate dynamics of such an algorithm, the state evolution (SE) has been proposed. If an...
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ISBN:
(纸本)9781457705953
It has been shown that approximate message passing algorithm is effective in reconstruction problems for compressed sensing. To evaluate dynamics of such an algorithm, the state evolution (SE) has been proposed. If an algorithm can cancel the correlation between the present messages and their past values, SE can accurately tract its dynamics via a simple one-dimensional map. In this paper, we focus on dynamics of algorithms which cannot cancel the correlation and evaluate it by the generating functional analysis (GFA), which allows us to study the dynamics by an exact way in the large system limit.
Massive multiple-input multiple-output (MMIMO) can significantly enhance the spectrum efficiency of cellular networks by deploying hundreds of active elements at the base stations and is envisaged to become the key te...
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ISBN:
(纸本)9781509021369
Massive multiple-input multiple-output (MMIMO) can significantly enhance the spectrum efficiency of cellular networks by deploying hundreds of active elements at the base stations and is envisaged to become the key technology in 5th generation (5G) cellular networks. However, the large number of antennas required brings about tremendous challenges for practical implementation, especially for separation of the multiplexed data. iterative approaches, such as Jacobi, Richardson, Gauss-Seidel (GS), successive overrelaxation (SOR), and symmetric successive overrelaxation (SSOR) have received great attention recently due to their low-complexity and high performance for signal detection. In this work, we provide a comprehensive review of recent progress in iterative based signal detection for massive MIMO systems. The system model of an iterative method based minimum mean square error (MMSE) signal detection is provided. The convergence behavior and complexity of the iterative approach based detectors are analyzed. Numerical results show that the iterative algorithm-based detectors can achieve a performance close to the classical MMSE detector with significantly less computational complexity.
Interference alignment(IA) with symbol extensions in the K-user multiple-input multiple-output (MIMO) interference channel(IC) is considered in this paper. Symbol extensions produce the channels of special structure. ...
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ISBN:
(纸本)9781467358293;9781467358309
Interference alignment(IA) with symbol extensions in the K-user multiple-input multiple-output (MIMO) interference channel(IC) is considered in this paper. Symbol extensions produce the channels of special structure. Most of existing approaches are limited in cases where the channels have some special structure, because they align the interference without preserving the dimensionality of the desired signal. For that reason, two novel iterative algorithms for IA with symbol extensions are proposed. The first algorithm designs transceivers for IA based on minimizing the maximum per-user mean square error(MSE) while preserving the dimensionality of the desired signal. Utilizing channel reciprocity, the second algorithm is proposed which is the constrained optimization problem. It maximizes each receiver's SINR while preserving the dimensionality of the desired signal. The simulation results show that the proposed algorithms not only achieve good performance in terms of BER performance but also achieve good performance on maximizing sum rate of the system.
In this paper, we introduce two iterative algorithms for the split feasibility problem in real Hilbert spaces by reformulating it as a fixed point equation. Under suitable conditions, weak and strong convergence theor...
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In this paper, we introduce two iterative algorithms for the split feasibility problem in real Hilbert spaces by reformulating it as a fixed point equation. Under suitable conditions, weak and strong convergence theorems are established. As a consequence, we obtain weak and strong convergence iterative sequences for the split equality problem introduced by Moudafi. The efficiency of the proposed algorithms is illustrated by numerical experiments. Our results improve and extend the corresponding results announced by many others.
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