Font Size: a A A

Adaptive Pilot Density Based Channel Estimation Algorithm For OFDM System

Posted on:2010-06-10Degree:MasterType:Thesis
Country:ChinaCandidate:N JiaFull Text:PDF
GTID:2218330368999986Subject:Communication and Information System
Abstract/Summary:PDF Full Text Request
Driven by multimedia based applications, anticipated future wireless systems will require high data rate capable technologies. Orthogonal frequency division multiplexing (OFDM; is a special case of multi-carrier transmission and it can accommodate high data rate requirement of multimedia based wireless systems.OFDM divides the available spectrum into a number ofoverlapping but orthogonal narrowband subchannels, and hence converts a frequency selective channel into a nonfrequencyselective channel.ISI is avoided bythe use of CP, which is achieved by extending an OFDMsymbol with some portion of its head or tail.Meanwhile IFFT and FFT are also used in the system, which made the modulation and the demodulation simple. However, the channel transfer function varies with times in the mobile communication. In order to improve communication efficiency and quality, it is necessary to make a dynamic estimation of the current transfer ftmetion.Based on the analyze and summarize to some relevant literature, this article introduces the developing history and research status of the orthogonal frequency division multiplexing, introduces the OFDM base-band transmission systems and the realization of the basic principles. Meanwhile, this article studys the channel estimation techniques of OFDM system: pilot distribution patterns, channel estimation and interpolation techniques.At the same time, it gives Adaptive Pilot Density Algorithm for OFDM channel estimation. The simulation results show that the algorithm can significantly reduce the pilot overhead, make system adapt to the changing of the environment, and raise the ability to transplant.
Keywords/Search Tags:OFDM, pilot, channel estimation, adaptive, pilot density
PDF Full Text Request
Related items