Narrowband AM interference cancellation for broadband multicarrier systems

We consider an overlay system where narrowband AM signals interfere with a broadband multicarrier system. To reduce the effect of the AM narrowband interference on the multicarrier system, we propose a low-complexity algorithm to estimate the AM narrowband interference. Analytical expressions for the performance of this estimator are derived and verified with simulations. The performance of this estimator, however, degrades when the number of interferers increases. To improve the algorithm, we adapt it such that the interferers are estimated in a successive way. The proposed estimators are able to produce accurate estimates of the frequencies, and track the time-varying amplitudes of the AM signals. The estimators can reduce the power of the AM signal to a level that is approximately 20 dB lower than the multicarrier power, independently of the AM signal power

Frequency offset estimation for KSP-OFDM

In this paper, we propose two ad hoc frequency offset (FO) estimation algorithms in a known symbol padding (KSP) orthogonal frequency-divisionmultiplexing (OFDM) system, where the guard interval is filled with pilot symbols. Besides those time domain pilot symbols, some additional pilot symbols are transmitted on the pilot carriers. The FO is estimated without any channel knowledge. One algorithm operates in the time domain (TD), while the other one operates in the frequency domain (FD). The interference from the unknown data symbols is much smaller in the FD than in the TD, especially for small FOs. As a result, the FD initialization algorithm results in a lower mean squared error (MSE). Both estimation algorithms reach the BER performance of a receiver with perfect knowledge about the FO

Near optimal iterative channel estimation for KSP-OFDM

In this paper, we propose an iterative 'turbo' channel estimation algorithm for known symbol padding (KSP) OFDM, where the guard interval is filled with pilot symbols. Additional pilot symbols are transmitted on some of the OFDM carriers. The channel estimation algorithm is based on the Expectation-Maximization (EM) algorithm. In the initialization phase of this iterative algorithm, the received time-domain samples are first converted to the frequency domain, and the initial channel estimate is based on the observation of the pilot carriers only. Then the EM-algorithm switches back to the time-domain and updates the channel estimates until convergence is reached. The proposed estimator performs very good: the MSE performance of the proposed estimator is close to the Cramer Rao lower bound (CRB) corresponding to the all pilots case, for the SNR region of practical interest, and the resulting bit error rate essentially coincides with the case of the perfectly known channel

Clipping Versus Symbol Switching for PAPR Reduction in Coded OFDM

In multicarrier systems, the transmitted time-domain signal exhibits large amplitude peaks. This peak-toaverage power ratio (PAPR) problem complicates the practical use of multicarrier systems: the amplifier used to transmit the signal saturates because of the large peaks and causes non-linear distortion. As this non-linear distortion frustrates severely the detection of the multicarrier signal, the average power of the multicarrier signal must be reduced such that the system operates in the linear part of the amplifier. However, this power reduction comes at the cost of a reduced capacity of the multicarrier system. Hence, several techniques were investigated to reduce the PAPR. In this paper, we compare two PAPR reduction techniques for coded OFDM using an iterative decoder, i.e. clipping and symbol switching. Clipping outperforms the symbol switching technique as for given PAPR reduction, a lower BER degradation is obtained. However, the clipping technique causes out-of-band radiation whereas the spectrum is not changed when using the symbol switching technique