Presentation on theme: "Channel Estimation for Mobile OFDM"— Presentation transcript:
1 Channel Estimation for Mobile OFDM Zhang Nan(62427P)
2 OUTLINE Basics of OFDM Channel Estimation Challenges of Channel Estimation in Mobile OFDMChannel Estimation TechniquesPerformance EvaluationConclusion
3 OFDM Overview Orthogonal Frequency Division Multiplexing To split a high-rate data stream into a number of lower rate streams that are transmitted simultaneously over a number of subcarrierIn OFDM systems, the spectrum of individual subcarrier is overlapped with minimum frequency spacing, which is carefully designed so that each subcarrier is orthogonal to the other subcarriers. The bandwidth efficiency of OFDM is another advantage.In the guard time , the OFDM symbol is cyclically extended to avoid intercarrier interference.
4 Advantages of OFDM Immunity to delay spread Symbol duration >> channel delay spreadGuard intervalResistance to frequency selective fadingEach subchannel is almost flat fadingSimple equalizationEach subchannel is almost flat fading, so it only needs a one-tap equalizer to overcome channel effect.Efficient bandwidth usageThe subchannel is kept orthogonality with overlap.
5 Challenges of OFDM (1/2) Synchronization Symbol synchronization Timing errorsCarrier phase noiseFrequency synchronizationSampling frequency synchronizationCarrier frequency synchronization
6 Challenges of OFDM (2/2) High Peak to Average Power Ratio (PAPR) It increased complexity of the analog-to-digital and digital-to-analog converters.It reduced efficiency of the RF power amplifier.
8 Three Large Groups of Channel Estimation Techniques (1/3) Channel estimation allows the receiver to approximate the effect of the channel on the signal.Pilot AssistedIt is the most straightforward way where symbols or tones known to the receiver, called pilots.Has a good performance in fast fading environments
9 Three Large Groups of Channel Estimation Techniques (2/3) Blind (without pilots)Based on channel statistics employment rather than on that of pilots.No Training sequences requiredMost existing blind channel estimation methods are based on second- or higher order statistics. It features relatively low complexity and a very fast convergence rate.Hard to implement on real time systems.
10 Three Large Groups of Channel Estimation Techniques (3/3) Semi-Blind (with initial pilot-based channel estimation and next channel tracking)Assumes an intermediate position and relies partly on pilots and partly on the use of channel statistics.A semi-blind competitive neural network based method of time-varying channel estimation is tested in this work.
11 Alogrithm Consider a multipath radio channel. Assume the Jakes model on each path.CNN based channel estimator
12 Competitive Neural Networks One of the most famous self-organizing in the neural networksA simple competitive network.One common learning rule simply adds the difference between the winning neuron and the input sequence to the winning neuron.
13 CNN Based OFDM Channel Estimator (1/2) The winner neuron is selected according to the Kohonen updated ruleThe dynamics of others neurons non-winners are defined as
14 CNN Based OFDM Channel Estimator (2/2) An estimate of the channel frequency response can be obtained from the weights of the neurons