A Research On Several Key Technologies In OFDM System With Low-Resolution ADC

Orthogonal frequency division multiplexing(OFDM)system operating in the millimeter wave(mm Wave)band,which can achieve multi-Gbps transmissions and overcome frequency-selective fading,has been extensively applied in wireless communication standards,such as IEEE 802.15.3c,IEEE 802.11 ad and the 5th generation mobile communication system(5G).Mm Wave systems require the analog-to-digital converters(ADCs)working in ultra high sampling rate.Thus,the low-resolution ADCs at mm Wave receivers will keep the power consumption and system costs at an acceptable level.Nevertheless,the low-resolution ADCs cause strong nonlinear distortion on the received signals.These problems pose a great challenge to the design of OFDM receiver.This paper focuses on a novel orthogonal frequency division multiplexing(OFDM)receiver architecture,which uses a low-resolution analog-to-digital converter(ADC)to oversample the received signal in time domain.For the proposed receiver,we consider an often-used transmission protocol with two phases.In the first phase,training OFDM symbols are transmitted for channel estimation.And in the second phase,informationconveying OFDM symbols are transmitted and detected using the previously obtained channel estimate.In this paper,we use a statistical method to characterize the nonlinear quantization model of the low-resolution ADC.Then we use variational Bayesian inference to solve the signal model based on ow-resolution ADC in order to obtain the algorithm of channel estimation and signal detection.It should be noticed that the oversampling receiver has multipath diversity effect.The receiving technology proposed in this paper can effectively deal with the color noise caused by oversampling,obtain diversity gain,and has excellent performance.Due to the limited number of reflectors and scatterers in mm Wave's propagation,there are only a few significant multipaths in the channel,thereby bringing about channel sparsity.The channel estimation technique proposed in this paper effectively characterizes the sparse pattern of the channel by using the parameterized Gaussian distribution and explores the channel sparsity by using variational Bayesian inference,which improves the performance of channel estimation significantly.With the popularity of high-speed trains,wireless communication technology in highspeed mobile environment has become a research hotpot.This paper proposes an OFDM receiver with low-resolution ADC working at time-variant channel.We use basis expansion models(BEM)to model the time-varying channel taps and design a joint algorithm of channel estimation and signal detection by using the variational Bayesian inference.In this algorithm,channel estimation and signal detection are completed in an OFDM symbol by inserting appropriate pilots.The receiver we proposed can adjust the BEM to match different Doppler spreads flexibly.Meanwhile,it is clear that the channel is sparse in the delay domain or rather jointly sparse.According to this,our receiver can improve the performance and reduce pilot overhead.To verify the performances of receivers proposed in this paper,many simulations are conducted.The simulation results show that the proposed receivers can remarkably outperform the counterparts.