A Strategy of Signal Detection for Performance Improvement in Clipping Based OFDM System

In this paper,the supervised Deep Neural Network(DNN)based signal detection is analyzed for combating with nonlinear distortions efficiently and improving error performances in clipping based Orthogonal Frequency Division Multiplexing(OFDM)ssystem.One of the main disadvantages for the OFDM is the high Peak to Average Power Ratio(PAPR).The clipping is a simple method for the PAPR reduction.However,an effect of the clipping is nonlinear distortion,and estimations for transmitting symbols are difficult despite a Maximum Likelihood(ML)detection at the receiver.The DNN based online signal detection uses the offline learning model where all weights and biases at fully-connected layers are set to overcome nonlinear distortions by using training data sets.Thus,this paper introduces the required processes for the online signal detection and offline learning,and compares error performances with the ML detection in the clipping-based OFDM systems.In simulation results,the DNN based signal detection has better error performance than the conventional ML detection in multi-path fading wireless channel.The performance improvement is large as the complexity of system is increased such as huge Multiple Input Multiple Output(MIMO)system and high clipping rate.

Complexity Effective Frequency and Sidelink Synchronization Algorithm for LTE Device-to-Device Communication Systems

Device-to-device(D2D)communication is considered as a major challenge in the long term evolution(LTE)network wherein devices directly communicate with each other.One of the key challenges in D2D sidelink is reliable and reduced-complexity synchronization.To address this issue,a computationally efficient sequential detection scheme for integer carrier frequency offset and sidelink identity is proposed in the LTE-D2D system.To perform the frequency offset detection without retrieving the sidelink identity,the conjugate relation between two primary sidelink synchronization sequences is exploited,which facilitates the detection tasks of frequency offset and sidelink identity to be decoupled.It is demonstrated from simulation results that the inherent property of the sidelink synchronization sequences is effectively used for joint detection of frequency offset and sidelink identity with significantly reduced complexity,compared to existing estimation schemes.