Capacity and BER performance improvement in integrated MIMO‐OFDM system using optimal power allocation, channel estimation, and turbo coding

Abstract

Summary Among communication systems, multiple input multiple output (MIMO) system has the capability of providing spectral efficiency, high data rates, diversity gain, and improved reliability. Suitably designed orthogonal frequency division multiplexing (OFDM) transmits the signal without inter symbol interference and multipath fading. Hence, MIMO‐OFDM is a strong candidate for 4G and 5G wireless systems. However, variations in signal‐to‐noise ratio (SNR) due to the random nature of the channel and poor capacity at low SNR are critical issues in conventional MIMO‐OFDM system. This paper explains how optimal power allocation (OPA), channel estimation, and coding improve the capacity and bit error rate (BER) performance of MIMO‐OFDM system. In OPA, the transmitter power is distributed adaptively to the channels based on the SNR statistics using singular value decomposition and water filling algorithm. In case of low SNR, less number of channels are selected for power allocation. Least squares (LS), minimum mean square error (MMSE), and least mean square (LMS) estimators are considered in comb type pilot channel estimation while turbo code is used with code rates of 1/2 and 1/3. From the simulation results, capacity improvement of 5 b/s/Hz and 11 b/s/Hz is observed for MIMO‐OFDM systems with four antennas and eight antennas, respectively. It is also found that performance of LMS estimator improved by 3.5‐dB SNR over LS and 1 dB SNR over MMSE. In this paper is shown how LMS estimator and 1/3 turbo code have been integrated with MIMO‐OFDM, and this has resulted in around 4‐dB SNR improvement over conventional MIMO‐OFDM.

Error Correction Using Hybrid Coding Algorithm for BER Reduction in MIMO-OFDM

“…2.0000×10 -5 1.0000×10 -4 1.0000×10 -5 4.0000×10 -6 10 6.3246×10 -6 3.1623×10 -5 3.1623×10 -6 1.2649×10 -6 method is analyzed with three different existing types of research namely AED [18], PC-CC [19] and TC-OPA [20]. The EC-HCA method is analyzed in terms of BER and PSNR.…”

“…Pyla [20] presented the optimal power allocation (OPA), coding, and channel estimation for enhancing the capacity and BER. The statistics of SNR using the singular value decomposition and water filling algorithm were used to perform the adaptive distribution of power in OPA.…”

“…In this analysis, both the transmitter and Table 3. Comparative analysis of PSNR for EC-HCA with 2 × 2 MIMO-OFDM Methods PSNR (dB) AED [18] 3.8 PC-CC [19] 2.9 TC-OPA [20] 5.3 EC-HCA 10.24 receiver are initialized with the 2 antennas. Fig.…”

“…Fig. 2 and Table 2 show the BER of EC-HCA with AED [18], PC-CC [19] and TC-OPA [20] for a 2 × 2 antenna.…”

An Uplink Channel Estimator Using a Dedicated Instruction Set for 5G Small Cells

“…Therefore, this study used the pilot-based OFDM channel estimation method. In the channel estimation at the DMRS, the LS [19] + Wiener interpolation [20] method is suitable for small cells due to its complexity and performance trade-off, and it is widely used in OFDM channel estimation.…”