- Tytuł:
- On the Comparison of Various Overhead Arrangements for Massive MIMO-OFDM Channel Estimation
- Autorzy:
-
Sure, P.
Bhuma, C. M. - Powiązania:
- https://bibliotekanauki.pl/articles/226978.pdf
- Data publikacji:
- 2014
- Wydawca:
- Polska Akademia Nauk. Czytelnia Czasopism PAN
- Tematy:
-
Massive MIMO-OFDM
time domain synchronous
comb type with cyclic prefix
grid type with cyclic prefix
denoising threshold
LS channel estimation - Opis:
- Massive multi input multi output (MIMO) systems incorporate orthogonal frequency division multiplexing (OFDM) technology to render high data rate services for future wireless communication applications. The channel estimator (CE) employed by a reliable massive MIMO-OFDM system requires huge amount of overhead in the form of known and null data transmissions, hence limiting the system spectral efficiency (SE). Often, CE design is a tradeoff between SE and system reliability. In this paper, CE with three different overhead arrangements, namely time domain synchronous (TDS), comb type with cyclic prefix (CTCP), 2D grid type with cyclic prefix (GTCP) are investigated and a GTCP based CE is proposed which offers both high SE and improved system reliability. The proposed CE uses autocorrelation based denoising threshold for channel impulse response (CIR) estimation and does not require any knowledge of channel statistics (KCS). A416 MIMO-OFDM system is simulated in a rayleigh fading channel environment with U-shaped doppler spectrum. From the bit error rate (BER) performance results in WiMax SUI-4, Advanced Television Technology Center (ATTC) and Brazil A channel environments, it is verified that the proposed CE with GTCP overhead and proposed denoising scheme, indeed improves both SE and system reliability. Hence it is suitable for application in all massive MIMO-OFDM systems.
- Źródło:
-
International Journal of Electronics and Telecommunications; 2014, 60, 2; 173-179
2300-1933 - Pojawia się w:
- International Journal of Electronics and Telecommunications
- Dostawca treści:
- Biblioteka Nauki