Research On Channel Estimation And Equalization Methods For Shortwave SIMO Communications

HF (High Frequency) communication, as one of the most important means ofcommunication, has attracted a lot of attention from researchers. On the other hand, therapid development of digital communication technology gives the traditionalcommunications like short-wave communication a new opportunity. MIMO(Multiple-Input Multiple-Output), as one of the main techniques of4G communication,has significant advantages of anti-jamming and increasing channel capacity.This paper first introduces the main channel characteristics of the short-wavecommunications. In the third chapter, applying with the diversity combiningtechnologies, including the maximum ratio combining, equal gain combining andselection combining, we analyzed the performance of shortwave SIMO (Single-InputMultiple-Output) communication through MATLAB simulation. When the channel stateinformation (CSI) is known to the receiver, the maximum ratio combining has theoptimal performance, which means it has the most signal-to-noise ratio gain and biterror rate (BER) is the least. Equal gain combining is sub-optimal and selectioncombining is the worst of these three combining schema. The reason for this result isthat MRC takes advantages of the priori information of the channel, such as channelfading amplitude, phase and time delay.However, in practice, the priori information is difficult to obtain. Thus, we need tothe channel estimation and channel equalization based on the characteristics of channels.Based on the needs of prior information, channel estimation and equalization methodscan be divided into three type, training sequence or pilot signal based methods,semi-blind and blind estimation methods. In the fourth chapter, we first introduced theMMSE (Minimum Mean Square Error) and least squares estimation, and analyzed theirperformance through MATLAB simulation. For the channel equalization methods, wefocused on the Decision-Directed algorithm, Sato algorithm, the Godard algorithm andfractionally spaced constant modulus algorithm (CMA). The performance of constantmodulus algorithm was analyzed as well. From the theoretical analysis and performancesimulation results, it has shown that HF communication performance can be greatly improved with multi-antenna technology.On the other hand, in the short-wave communication, since the ionospherereflections will result in a large time delay. With a finite impulse response (FIR) filter,the channel tap coefficients will only have a few non-zero values. Therefore, HFchannel is a sparse multipath channel. For sparse multipath channels, the simulationresults showed that the traditional channel estimation methods, such as least-squaresalgorithm, will get a large number of non-zero values, which is inconsistent with theactual channel. Therefore, to solve this problem, this paper proposed the use oflpnorm constraint, FOCUSS and other sparse algorithm as a solution.