This paper proposed a new OFDM scheme called damped zero-pseudorandom noise orthogonal frequency division multiplexing (DZPN-OFDM) scheme. In the proposed scheme, ZPN-OFDM non-zero part is damped to reduce its energy, thus the mutual interference power in-between the data and training blocks with conservative the pseudo-noise conventional properties required for channel estimation or synchronization. The motivation of this paper is the OFDM long guard interval working in wide dispersion channels, whereas a significant energy is wasted when the conventional ZPN-OFDM is used as well as the BER performance is also degraded. Moreover, the proposed scheme doesn’t duplicate the guard interval to solve the ZPN-OFDM spectrum efficiency loss problem. Both detailed performance analysis and simulation results show that the proposed DZPNOFDM scheme can, indeed, offer significant bit error rate, spectrum efficiency and energy efficiency improvement.
The large variability of communication properties of underwater acoustic channels, and especially the strongly varying instantaneous conditions in shallow waters, is a challenge for the designers of underwater acoustic communication (UAC) systems. The use of phase modulated signals does not allow reliable data transmission through such a tough communication channel. However, orthogonal frequency-division multiplexing (OFDM), being a multi-carrier amplitude and phase modulation technique applied successfully in the latest standards of wireless communications, gives the chance of reliable communication with an acceptable error rate. This paper describes communication tests conducted with the use of a laboratory model of an OFDM data transmission system in a shallow water environment in Wdzydze Lake.
To overcome the detrimental influence of α impulse noise in power line communication and the trap of scarce prior information in traditional noise suppression schemes , a power iteration based fast independent component analysis (PowerICA) based noise suppression scheme is designed in this paper. Firstly, the pseudo-observation signal is constructed by weighted processing so that single-channel blind separation model is transformed into the multi-channel observed model. Then the proposed blind separation algorithm is used to separate noise and source signals. Finally, the effectiveness of the proposed algorithm is verified by experiment simulation. Experiment results show that the proposed algorithm has better separation effect, more stable separation and less implementation time than that of FastICA algorithm, which also improves the real-time performance of communication signal processing.