Study of Various Channel Estimation Techniques in OFDM Mobile Wireless Channel
01 Feb 2015-Journal of emerging technologies and innovative research (JETIR(www.jetir.org))-Vol. 2, Iss: 2, pp 271-278-271-278
TL;DR: In this paper, the authors used pilot sequences to estimate the time-varying channel frequency response for the OFDM symbols in a mobile wireless channel with low complexity, which is a useful channel estimation technique for accurate estimation of the transmitted information.
Abstract: In modern world error free transmission is one of the main aims in wireless communications. As the increase in multimedia application, bulky data is being transmitted over wireless communications. Due to the effect of channel fading and the Doppler shifts caused by user mobility, a common problem in the wireless systems, additional technologies are needed to be combat multipath propagation fading and Doppler shifts. The time-variant channel estimation is one of such a crucial technique used to improve the performance of the modern wireless systems with Doppler spread and the multipath spreading. Channel estimation is usually done by estimating the time-varying channel frequency response for the OFDM symbols. . In order to reduce complexity of MIMO system, various detection algorithm such as Zero Forcing (ZF), Minimum Mean Square Error (MMSE), Maximum Likelihood (ML) and LMMSE is studied that reduce Bit Error Rate (BER) by using spatial multiplexing. In time-variant channel estimations using the pilot Sequences technique is a useful channel estimation techniques in mobile wireless communication for accurately estimation of the transmitted information. The main advantage of pilot sequences is to allowing the more accurate representation of the high mobility mobile wireless channels with low complexity. The main goal is to test the most recent proposed method, time-variant estimation of the channel using pilot sequences.
••22 Mar 2017
TL;DR: Estimating the channel parameters for conventional MIMO and massive MIMo based on training-based and blind channel estimation techniques wherein the performance of both is compared is compared.
Abstract: Multiple-input multiple-output (MIMO) technology is becoming mature in wireless communication systems. It has led to third and fourth generation wireless systems, which has been providing good range, reliability and higher data rates. For the increased demand of much higher data rates, coverage, spectral efficiency, capacity and reduced latency, the evolution of the next generation i.e., the fifth generation technology is necessary. Massive MIMO technology is one of the most promising solution for the above-mentioned challenge. In massive MIMO, the base station is incorporated with hundreds to thousands of antenna array wherein the degrees of freedom can be exploited and the energy can be efficiently used due to the fact that the extra antennas at the base station helps focus the energy into the smaller regions of space. To reap the benefits provided by the extra antennas, the channel information is necessary which makes it possible to have a reliable communication. Therefore, to acquire the channel knowledge, channel state information is required at the base station and estimating the channel parameters plays an important role. In this paper, we concentrate on estimating the channel parameters for conventional MIMO and massive MIMO based on training-based and blind channel estimation techniques wherein the performance of both is compared.
Cites background from "Study of Various Channel Estimation..."
...error (MMSE), zero forcing (ZF) and least square (LS) techniques in , ....
••01 Jan 2022
TL;DR: In this article, the BER performance and outage capacity of MIMO and massive mIMO on Rayleigh, Rician and Nakagami channels are compared. And the performance analysis between MIMI and Massive MIMOs is analyzed with different channels corresponding to the output and result obtained.
Abstract: Multiple Input Multiple Output (MIMO) provides an environment in wireless communication that offers simple antennas and resource allocation is simplified utilizing Time Division multiplexing. MIMO overcomes bandwidth restrictions with its channel state information and multiple antennas. Massive MIMO uses large-scale antenna systems and are capable of improving the channel capability. Extra antennas improve the throughput and energy efficiency. The performance analysis between MIMO and Massive MIMO is analyzed with different channels corresponding to the output and result obtained. In this paper, the BER performance and outage capacity of MIMO and Massive MIMO on Rayleigh, Rician and Nakagami channels are compared.