The closed-loop transmit diversity technique is used to increase the capacity of the downlink channel in multiple-input-multiple-output (MIMO) communication systems.The WCDMA standard [1] endorsed by 3GPP [2] adopts two modes of downlink closedloop schemes based on partial channel information that is fed back from the mobile unit to the base station through a low-rate uncoded feedback bit stream. In this article, some soft reconstruction techniques are introduced to improve the performance of Mode 1 of 3GPP, by taking advantage of the redundancy available in the channel information. We propose some algorithms for reconstruction of beamforming weights in the base station.The performance is examined in a simulated 3GPP framework in the presence of different feedback error rates at various mobile speeds. It is demonstrated that the proposed algorithms have substantial gain over the conventional approach for low to high mobile speeds. Index TermsClosed-loop transmit diversity, channel feedback, channel state information (CSI), downlink communication, FDD WCDMA, mode 1 of 3GPP, joint source-channel coding
A key element for many fading-compensation techniques is a (long-range) prediction tool for the fading channel. A linear approach, usually used to model the time evolution of the fading process, does not perform well for long-range prediction applications. In this article, we propose an adaptive fading channel prediction algorithm using a sum-sinusoidal-based state-space approach. This algorithm utilizes an improved adaptive Kalman estimator, comprising an acquisition mode and a tracking algorithm. Furthermore, for the sake of a lower computational complexity, we propose an enhanced linear predictor for channel fading, including a multi-step linear predictor and the respective tracking algorithm. Comparing the two methods in our simulations show that the proposed Kalman-based algorithm significantly outperforms the linear method, for both stationary and non-stationary fading processes, and especially for long-range predictions. The performance and the self-recovering structure, as well as the reasonable computational complexity, makes the algorithm appealing for practical applications 1 .
A single-pixel camera for THz imaging has been proposed in [1]. In this article, we propose a new design for a single-detector THz imaging system based on Compressive Sampling (CS), which does not need raster scanning of the object in front of the THz beam. We exploit a time-efficient and costeffective design to acquire the CS measurements. As a result, the image acquisition time in the proposed imaging system is only limited to the speed of the THz detector. The proposed approach is applicable to other types of imaging as well.
Abstract-In this article, a time-domain calibration procedure is proposed for pulsed Terahertz Integrated Circuits (TIC) used in onchip applications, where the conventional calibration methods are not applicable. The proposed post-detection method removes the unwanted linear distortions, such as interfering echoes and frequency dispersion, by using only one single-port measurement. The method employs a wave-transfer model for analysis of the TIC, and the model parameters are obtained by a proposed blind estimation algorithm. A complete implementation of the method is demonstrated for a fabricated TIC, when used in an on-chip sensing application. The features of interest in the measured signal, such as absorption lines, can be masked or weakened by the distortion of the THz signal happening in a TIC. The proposed signal recovery approach improves the detection of those otherwise hidden features, and can significantly enhance the performance of existing TICs. To show the effectiveness of the proposed de-embedding method, numerical results are presented for simulated and measured signals. The method presented in this article is enabling for accurate TIC applications, and can be utilized to optimally design novel TIC structures for specific purposes.
The closed-loop transmit diversity technique is used to improve the performance of the downlink channel in MIMO communication systems. In these closed-loop systems, feedback delay and feedback error, as well as the sub-optimum reconstruction of the quantized feedback data, are the usual sources of deficiency. We address the efficient reconstruction of the beamforming weights in the presence of the feedback imperfections, by exploiting the residual redundancies in the feedback stream. Focusing on the issue of feedback delay, we propose two approaches to improve the performance. One is based on using a channel predictor at the receiver to compensate for the delay, and using a joint source-channel coding (JSCC) method similar to our previous work [2] to compensate for the feedback error. Another approach deals with the feedback imperfections in a unified reconstruction algorithm using JSCC techniques. Furthermore, we introduce the concept of Blind Antenna Verification which can substitute the conventional Antenna Weight Verification process without the need for any training data. The closed-loop mode 1 of the 3GPP standard is used as a benchmark, and the performance is examined within a Wideband-CDMA simulation framework. It is demonstrated that the proposed algorithms outperform the conventional methods at all mobile speeds, and are suitable for the implementation in practice.
Long-range prediction of fading in mobile systems is the key element for many fading-compensation techniques. A linear approach, which is usually used to model the time evolution of the fading process, does not perform well for long-range prediction. In this article, we propose an adaptive channel prediction algorithm by using a novel statespace model for the fading process. Our simulations show that this algorithm significantly outperforms the conventional linear method, for both stationary and non-stationary fading processes, especially for longrange predictions 1 .
Abstract-The closed-loop transmit diversity technique is used to improve the performance of the downlink channel in MIMO communication systems. The WCDMA standard endorsed by 3GPP adopts two modes of downlink closed-loop schemes based on partial channel state information. The information is fed back from the mobile unit to the base station through a low-rate uncoded feedback bit stream. Previously [1], we addressed the efficient reconstruction of the beamforming weight in the presence of feedback error, with the constraint of a constant transmit power.In this article, the issue of feedback delay is also considered. Using joint source-channel coding techniques, a reconstruction algorithm is introduced to improve the performance of mode 1 of 3GPP in the presence of feedback error and delay, by taking advantage of the redundancy available in the bitstream of channel state information. We also introduce the novel concept of Blind Antenna Verification. It can substitute the conventional Antenna Weight Verification process without the need to any training data. The performance is examined within a simulated 3GPP framework. It is demonstrated that the proposed algorithms have substantial gain over the conventional method for low, moderate and high mobile speeds. The proposed approaches are applicable to other feedback schemes as well 1 .
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.