Optimization And Simulation Of Filtered OFDM Subband Filter

As one of 5G dynamic soft air interface algorithm,Filtered-OFDM is a sub-band-based filtering algorithm,which is based on non-orthogonal sub-band filter waveform to meet the 5G rich business scenario.The basic principle is to divide the system bandwidth into several sub-bands.There is a narrower guard interval between the subbands,and the flexible frequency range that OFDM can not use is flexible.Each subband configures different parameters according to a specific service,and each subband is filtered by an adaptive filter respectively to better decouple the subbands.Thus,while satisfying the 5G rich service,LTE-OFDM systems are reduced in the presence of high out-of-band leakage and the sidelobe attenuation is increased by about 23 dB,as a result the spectrum utilization is improved.The Filtered-OFDM system waveform is a superimposed transmission in time domain of each sub-band.When the sub-band transmission waveforms are in phase or close to each other,the peaks of the waveforms will be superposed,resulting in larger instantaneous peak power,which will make the sub-band signal into the nonlinear region of the power amplifier,causing serious distortion of the signal,resulting in non-linear distortion of the signal.Therefore,DFT-s F-OFDM(DFT-s F-OFDM)is adopted as the discrete Fourier expansion filter,and the improved waveform optimizes the higher peak-to-average PAPR of the Filtered-OFDM waveform itself.Also,the filtering process is possible to increase the signal-to-average ratio of the signal.To reduce the instantaneous peak-to-average ratio,the circulating limiting filter at the transmitting end is used to achieve a gain with a peak-to-average ratio of nearly 2 dB.For the Filtered-OFDM waveform,each sub-band needs to be filtered separately.Therefore,the conventional filtering method using the Least Mean Square(LMS)and the Recursive Least Square(RLS)algorithm obviously does not meet the standard.Normalized SAF(NSAF)can improve the problem of input colored signals,but when the system background noise is high,the signal will appear higher deviation.Therefore,an improved normalized subband Adaptive Filter Optimization Algorithm(Improved NSAF,INSAF)is mentioned.The INSAF algorithm uses the least mean square Euclidean norm to minimize the current weight vector and the past p weight vectors,preventing the tap weights from fluctuating significantly.In order to achieve the compromise between convergence speed and steady state offset,a variable step-size adaptive filter optimization algorithm(VSS-INSAF)is proposed.The core of the algorithm is the equal power between sub-band system noise and the sub-band a posteriori error signal.For further analysis,combination step of the affine projection adaptive filter CSS-IAPSAF,the use of hyperbolic function to modify the mixing step parameters to obtain the combined step size,resulting in lower steady-state disorders,about a 5dB reduction.The proportioned combined step affine projection adaptive filter,PCSS-IAPSAF,combines IAPSAF and CSS-IAPSAF better,and uses the positive definite matrix to configure the calculated tapped weights,and obtains the distribution of the step size according to the weight proportion.So in the case of accelerating the convergence rate,the steady-state offset is further optimized,reducing about 4dB.