We investigate the problem of channel estimation in an orthogonal frequency-division multiplexing (OFDM) system plagued by unknown narrowband interference (NBI). Such scenario arises in many practical contexts, including cellular applications and emerging spectrum sharing systems, where coexistence of different types of wireless services over the same frequency band may result into remarkable co-channel interference. Estimation algorithms devised for conventional OFDM transmissions are expected to suffer from significant performance degradation in the presence of NBI. To overcome this difficulty, in the present work we follow a novel pilot-aided approach where the interference power on each pilot subcarrier is treated as a nuisance parameter which is averaged out from the corresponding likelihood function. The latter is then maximized in an iterative fashion according to the expectation-maximization (EM) principle or by applying the Jacobi-Newton algorithm. The resulting schemes have affordable complexity and are inherently robust to NBI. Their accuracy is investigated by means of computer simulations and compared with the relevant Cramer- Rao bound.
Channel estimation in OFDM systems with unknown interference
MORELLI, MICHELE;MORETTI, MARCO
2009-01-01
Abstract
We investigate the problem of channel estimation in an orthogonal frequency-division multiplexing (OFDM) system plagued by unknown narrowband interference (NBI). Such scenario arises in many practical contexts, including cellular applications and emerging spectrum sharing systems, where coexistence of different types of wireless services over the same frequency band may result into remarkable co-channel interference. Estimation algorithms devised for conventional OFDM transmissions are expected to suffer from significant performance degradation in the presence of NBI. To overcome this difficulty, in the present work we follow a novel pilot-aided approach where the interference power on each pilot subcarrier is treated as a nuisance parameter which is averaged out from the corresponding likelihood function. The latter is then maximized in an iterative fashion according to the expectation-maximization (EM) principle or by applying the Jacobi-Newton algorithm. The resulting schemes have affordable complexity and are inherently robust to NBI. Their accuracy is investigated by means of computer simulations and compared with the relevant Cramer- Rao bound.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
