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In orthogonal frequency division multiplexing (OFDM) based cellular systems, co-channel interference (CCI) from adjacent interfering base stations (BSs) would greatly degrade the bit error rate (BER) performance of cell-border users. In the previous work, a blind single antenna interference cancellation (SAIC) algorithm named least mean square-blind joint maximum likelihood sequence estimation (LMS-BJMLSE)...
Orthogonal frequency division multiplexing (OFDM) delivers high data transmission rate and forms the basis of Beyond 3G. The channel estimation is imperative for the implementation of OFDM. Cyclic Prefix (CP) based block Recursive Least Squares (RLS) channel estimation algorithm has been proposed for OFDM systems but it increases computational complexity. In this paper, we propose a block LMS (Least...
A novel channel estimation scheme based on superimposed training is proposed for space time block coded (STBCO) multi-band (MB) orthogonal frequency division multiplexing (OFDM) ultra-wideband (UWB) systems. The optimal training symbols are derived with respect to the least square (LS) channel estimate mean square error (MSE). Simulation shows that the proposed scheme benefits much higher effective...
Effects of improved channel estimation are studied for a proposed IEEE 802.11n OFDM MIMO system. Three channel estimation methods are considered: maximum likelihood (ML), time-domain truncation (TDT) and model-based (MB). TDT and MB are particularly useful when the channel delay spread is short. For an MMSE receiver, MB shows a 1-2.5 dB improvement over ML on the packet error rate performance for...
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