Study On Semi-blind Channel Estimation Algorithm Based On Precoding For OFDM System

IntroductionOrthogonal frequency-division multiplexing is a promising candidate for nextgeneration high-speed wireless multimedia communication system due to its highdata rate, high spectral efficiency, and robust to frequency-selective channels,and itis regarded as the key technology for the next mobile communication system., whichis equivalent to the status of CDMA in 3G presently.In the mobile communication system, the receiver can adopt incoherentdetection or coherent detection. The incoherent detection has the merits of nonrequirementof channel state information and low complexity. The shortage is that itis only suitable for low data rate transmission system. Its performance is not as goodas that of OFDM systems based on coherent detection. For realizing the coherentdetection, channel estimation is needed at the receiver so as to detect symbols withthe known channel state information. So wireless channel estimation is an importantaspect in wireless communication domain, which is the basis of coherent detection,demodulation and cannel equalization. It's a significant component to guarantee thequality of communication, and it is also very important for OFDM technique torealize data communication at high speed.The channel estimation methods can be divided into three categories. The firstone is the channel estimation method based on pilot or trained sequence. This kindof algorithm has good capability and is easy to realize. The transmition velocitydecreases because the introduced pilot symbols or trained sequence occupy someuseful bandwidth. The second one is blind channel estimation, which is based on thelimited characters of the transmitted information symbols and their statistical trait.This kind of method does not need pilot symbols or trained sequence, so thebandwidth is saved and it can improve the spectrum utilization efficiency. But it hasthe disadvantages of slow convergence, high complexity. The third one is the semiblindchannel estimation method by using the information from blind channelestimation algorithm and known sampling symbols to finish channel estimation. Itsolves the problems of spectrum waste from channel estimation based on pilotsymbols or trained sequence and slow convergence of blind channel estimation methods. So the semi-blind channel estimation algorithm is regarded to be apromising way for channel estimation.The improved semi-blind channel estimation based on precoding for OFDM systemsIn this paper, the blind channel estimation algorithm based on precoding forOFDM system is studied in detail. Under the precoding, we present a semi-blindchannel estimation algorithm to improve the Subspace-based blind channelestimation algorithm, and this semi-blind channel estimation algorithm onlyintroduces a pilot symbol in an OFDM block. So the proposed algorithm has goodspectra efficiency and fast convergence.In this dissertation, under the bpsk and high-order modulation methods, theprinciple of the OFDM system with precoding is investigated. It is distinct fromtypical OFDM systems in that a precoder is present before the IDFT module, unlikeother coded OFDM schemes, the percoder in our method is a simple lineartransform, only adding one symble of an OFDM block to the whole block, thecorrelation structure imposed on the transmitted blocks can be exploited at thereceiver to recover the channel via a computationally very simple procedure. Itpermits to directly read the channel (frequency response) from the correlation of theoutput of each subchannel. It does not introduce redundancy to the block, nor doeschange the block length.The algorithm above purely extracts CSI from a single column of thecovariance matrix, which greatly limits the performance accuracy of the algorithm.The blind channel estimation based on subspace is studied to solve the problem,which means a nonredundant linear percoder is applied at the transmitter and CSI(channel state information) is possessed in all entries of the signal covaviancematrix, comparing with the method which purely extract CSI from a single columnof the covaviance matrix, numerical simulations clearly show the improvedperformance. The subspace based blind channel estimation is applicable to a moregeneral percoder and a detailed precoder design is available in this dissertation,including Distortion Constraint, Power Constraint and Symble Error Constraint.From the discussion, it is seen that there exists a compromise between channelestimation error and data detection error. Therefore, different considerations should be made under different situations.But the blind channel estimation algorithm converges slowly, a new semi-blindmethod is proposed to overcome the problem by using gradient-based variableforgating factor RLS algorithm (GVFF-RLS) instead of RLS algorithm to computethe signal covariance matrix, this new algorithm provides fast tracking and smallmean square error. This algorithm only introduces a pilot symbol, so it has highspectra efficiency. which uses the product of current channel inplulse response andthe pilot symbol to estimate the current receiving symbol, then utilizing thedifference between the current receiving symbol and the estimated value to ascertainthe mean-square error. The control mechanism can be explained as follows: Thegradient turns into the positive value whenever there is a large model error; On theother hand, the gradient turns into the negative value when the error is reduced to acertain level. The simulation results prove under the time-variant slow fadingchannel, its error performance is improved and the rate of convergence is better thanthe constant forgetting factor algorithm.In this paper, the channel estimation method with noise suppression is adopted.Because the accuracy of the channel response estimated from a variety of algorithmsis affected by proper error and noise, to descrease these errors, the low-pass filtercan be adopted. It could weaken the affection of the noise, which means the channellength is enforced in the time domain. This process is known as denoising, whichcan improve the estimation accuracy.ConclusionConclusions and Future WorkIn this paper, the blind channel estimation algorithm based on precoding isstudied. A new semi-blind algorithm is proposed to overcome the problem of slowconvergence, using GVFF-RLS instead of RLS to compute the signal covariancematrix. Numerical simulations clearly show the improved performance whenproposed method is compared with the existing method.OFDM Synchronisation problem is not discussed in this paper, in the future,combing with Synchronisation problem, how to find semi-blind channel estimationwith fast convergence which apply to the fast fading channel is needed further study.