Performance of Channel Estimation in MIMO-OFDM Systems

Abstract

Abstrak Paper ini mensimulasikan kinerja metode estimasi kanal fading pada orthogonal frequency division multiplexing-multiple input multiple output (OFDM-MIMO), least squares (LS) dan minimum mean squared error (MMSE). Channel impul response (CIR) kanal fading dibutuhkan untuk mengatasi intersymbol interference (ISI Kata kunci: block-comb type, LS, MIMO-OFDM, MMSE Abstract This paper presented the performance of faded channel estimation method on orthogonal frequency division multiplexing-multiple input multiple outputs (OFDM-MIMO) i.e. least squares (LS) and minimum mean squared error (MMSE). Channel impuls response (CIR) was required to overcome the intersymbol interference (ISI). Channel impuls response information was obtained from channel estimation processing. Iterance simulation used monte-carlo technique to determine the performance of bit error rate (BER) and mean squared error (MSE).Simulation results show that the mean squared error performance on MIMO system was better than the SISO system. On MMSE channel estimation, the MIMO 2Tx-2Rx system provided ± 2 dB improvement that compared to SISO system at value of MSE 10 -2 . Furthermore, MMSE channel

A Comparative Performance Study of OFDM System with the Implementation of Comb Pilot-Based MMSE Channel Estimation

“…It is clear that the MMSE channel estimator gives better BER performance than the LS estimator in data transmission over the Rayleigh channel. Similar results were observed in [12,14] in studying the performance of channel estimation methods for SISO and MIMO OFDM system. This result is consistent with earlier studies [9,13].…”

“…The authors in [10] shown that among the MMSE and ZF equalizers, the BER performance of MIMO OFDM system is better for MMSE equalizer. Pramano and Triyono [12] found that the performance of MIMO system is better than SISO system and the MMSE estimator produced better performance than low complexity LS estimator. In another study [13], it was concluded that block type pilot-based channel estimation is better for slow fading channel while comb type pilot-based channel estimation shows better performance in fast fading environment.…”

Low Complexity Sparse Channel Estimation Based on Compressed Sensing

“…S. Pramono has improved the estimation accuracy through applying multiple input multiple output (MIMO) to channel estimation [7]. In literatures [8], a reconfigurable and sparse array antenna was proposed, which can also improve the estimation accuracy.…”

A novel delay dictionary design for compressive sensing-based time varying channel estimation in OFDM systems

“…The performance of high data rate transmissions over wireless fading channels severely degraded due to the multi path effects which causes inter symbol interference (ISI). In order to combat the fading effects, OFDM has been widely adopted to wireless transmission [1][2][3][4][5][6][7][8]. The multipath propagation causes a time varying channel state information (CSI), which needed to be predicated or estimated using channel estimation techniques in order to recover the transmitted signal.…”