Recurrent Neural Network Based Narrowband Channel Prediction

In this contribution, the application of fully connected recurrent neural networks (FCRNNs) is investigated in the context of narrowband channel prediction. Three different algorithms, namely the real time recurrent learning (RTRL), the global extended Kalman filter (GEKF) and the decoupled extended Kalman filter (DEKF) are used for training the recurrent neural network (RNN) based channel predictor. Our simulation results show that the GEKF and DEKF training schemes have the potential of converging faster than the RTRL training scheme as well as attaining a better MSE performance

Wideband Channel Estimation and Prediction in Single-Carrier Wireless Systems

Abstract—In this contribution wideband channel estimation and prediction designed for single-carrier wideband wireless communications systems are investigated. Specifically, the single-carrier wideband pilot signal received by the receiver is first converted to the frequency-domain. Then, the envelope of the channel transfer function (CTF) is estimated in the frequency-domain, in order to reduce the effects of background noise on the channel prediction step to be invoked. Finally, channel prediction is carried out based on the estimated CTF in the frequency-domain, where a Kalman filter assisted long-range channel prediction algorithm is employed. Our simulation results show that for a reasonable signal-to-noise ratio (SNR) value the proposed frequency-domain based wideband channel estimator is capable of efficiently mitigating the effects of the background noise, hence enhancing the performance of wideband channel prediction

Understanding the performance of the electric power industry in China

© 2012 The Earth Institute at Columbia University and the Massachusetts Institute of Technology.Despite three decades of reform, China's electricity sector is still organized by a “new reformed plan” where capacity investment has been liberalized but prices and production remain controlled. This paper examines the impact of the current plan prices on end-users with reference to the OECD and how the plan price of electricity supply is formed. We argue that the plan price is set in an attempt to balance the interests of the public and the power industry. We find that China's industries do not pay a cheaper price for electricity than the West, and the plan price is formed through bargain between the firm and the state, which allows the firm to have a soft price constraint on its costs

Effects of Rate Adaption on the Throughput of Random Ad Hoc Networks

The capacity of wireless ad hoc networks has been studied in an excellent treatise by Gupta and Kumar [1], assuming a fixed transmission rate. By contrast, in this treatise we investigate the achievable throughput improvement of rate adaptation in the context of random ad hoc networks, which have been studied in conjunction with a fixed transmission rate in [1]. Our analysis shows that rate adaptation has the potential of improving the achievable throughput compared to fixed rate transmission, since rate adaptation mitigates the effects of link quality fluctuations. However, even perfect rate control fails to change the scaling law of the per-node throughput result given in [1], regardless of the absence or presence of shadow fading. This result is confirmed in the context of specific adaptive modulation aided design examples