This paper focuses on a new identification method for multiple-inputsingleoutput (MISO) Wiener nonlinear systems, in which the static nonlinear block is assumed to be a polynomial. The basic idea is to establish a M...
详细信息
This paper focuses on a new identification method for multiple-inputsingleoutput (MISO) Wiener nonlinear systems, in which the static nonlinear block is assumed to be a polynomial. The basic idea is to establish a MISO Wiener nonlinear identification model with polynomial nonlinearities by means of the key term separation principle. Then, a new identification method based on Levenberg-Marquardt iterative (LMI) search techniques, which can make full use of all the measured input and output data, but also automatically change the search step-size according to the change values of the quadratic criterion function, is derived to obtain an accurate and fast parameter estimation of the model. Finally, the simulation results demonstrate the efficacy of this method.
The concept of reconfiguring wireless propagation environments using intelligent reflecting surfaces (IRS)s has recently emerged, where an IRS comprises of a large number of passive reflecting elements that can smartl...
详细信息
The concept of reconfiguring wireless propagation environments using intelligent reflecting surfaces (IRS)s has recently emerged, where an IRS comprises of a large number of passive reflecting elements that can smartly reflect the impinging electromagnetic waves for performance enhancement. Previous works have shown promising gains assuming the availability of perfect channel state information (CSI) at the base station (BS) and the IRS, which is impractical due to the passive nature of the reflecting elements. This paper makes one of the preliminary contributions of studying an IRS-assisted multi-user multiple-inputsingle-output (MISO) communication system under imperfect CSI. Different from the few recent works that develop least-squares (LS) estimates of the IRS-assisted channel vectors, we exploit the prior knowledge of the large-scale fading statistics at the BS to derive the Bayesian minimum mean squared error (MMSE) channel estimates under a protocol in which the IRS applies a set of optimal phase shifts vectors over multiple channel estimation sub-phases. The resulting mean squared error (MSE) is both analytically and numerically shown to be lower than that achieved by the LS estimates. Joint designs for the precoding and power allocation at the BS and reflect beamforming at the IRS are proposed to maximize the minimum user signal-to-interference-plus-noise ratio (SINR) subject to a transmit power constraint. Performance evaluation results illustrate the efficiency of the proposed system and study its susceptibility to channel estimation errors.
In this paper, we propose a reduced complexity resource allocation technique for the downlink of multiple-inputsingle-output Orthogonal Frequency Division multiple-Access (MISO-OFDMA) system. The proposed algorithm e...
详细信息
ISBN:
(纸本)9781479923588
In this paper, we propose a reduced complexity resource allocation technique for the downlink of multiple-inputsingle-output Orthogonal Frequency Division multiple-Access (MISO-OFDMA) system. The proposed algorithm efficiently allocates frequency resources among users per subcarrier such that a group of users are simultaneously assigned on the same subcarrier with minimum amount of interference through zero forcing beamforming (ZFBF). The proposed algorithm considers quality of service (QoS) in terms of minimum user rate for each user and preserves fairness among users. QoS plays a key role in fulfillment of users demand of high bandwidth data services in modern wireless systems. Simulation results reveals that the proposed algorithm outperforms other reference algorithms in terms of sum rate, minimum user rate, QoS and preserves a very good fairness performance. Complexity of proposed algorithm is measured by execution time needed and compared to reference algorithms. Simulation results show a further reduction in complexity.
This paper deals with modeling and parameter identification of multiple-inputsingle-output Wiener nonlinear systems. The basic idea is to construct a multiple-inputsingle-output Wiener nonlinear model and to derive ...
详细信息
This paper deals with modeling and parameter identification of multiple-inputsingle-output Wiener nonlinear systems. The basic idea is to construct a multiple-inputsingle-output Wiener nonlinear model and to derive the gradient-based iterative algorithm for the proposed model. The proposed method has been applied to identify the parameters of a glutamate fermentation process. The results of real data simulation show that this method is effective. (C) 2013 Elsevier Ltd. All rights reserved.
The optimal transmission strategy of a multiple-inputsingle-output wireless communication link is studied in which the receiver has full channel state information and the transmitter has only long-term channel state ...
详细信息
ISBN:
(纸本)0780374029
The optimal transmission strategy of a multiple-inputsingle-output wireless communication link is studied in which the receiver has full channel state information and the transmitter has only long-term channel state information in terms of the channel covariance matrix. A necessary and sufficient condition for the optimal eigenvalues of the transmit covariance matrix is presented. A necessary and sufficient condition for achieving capacity when transmitting in m directions is developed. Main questions regarding the system design are answered using these conditions. It is shown how the optimal number of transmit antennas can be computed to achieve full spatial diversity given the channel covariance matrix. The maximum number of required parallel data streams is computed and a transmit diversity function is defined in order to obtain a measure for the available spatial diversity.
暂无评论