Machine Learning-Based Channel State Estimators for 5G Wireless Communication Systems

For a 5G wireless communication system,a convolutional deep neural network(CNN)is employed to synthesize a robust channel state estimator(CSE).The proposed CSE extracts channel information from transmit-and-receive pairs through offline training to estimate the channel state information.Also,it utilizes pilots to offer more helpful information about the communication channel.The proposedCNN-CSE performance is compared with previously published results for Bidirectional/long short-term memory(BiLSTM/LSTM)NNs-based CSEs.The CNN-CSE achieves outstanding performance using sufficient pilots only and loses its functionality at limited pilots compared with BiLSTM and LSTM-based estimators.Using three different loss function-based classification layers and the Adam optimization algorithm,a comparative study was conducted to assess the performance of the presented DNNs-based CSEs.The BiLSTM-CSE outperforms LSTM,CNN,conventional least squares(LS),and minimum mean square error(MMSE)CSEs.In addition,the computational and learning time complexities for DNN-CSEs are provided.These estimators are promising for 5G and future communication systems because they can analyze large amounts of data,discover statistical dependencies,learn correlations between features,and generalize the gotten knowledge.

Design and Implementation of Initial Cell Search in 5G NR Systems

The initial cell search plays an important role during the process of downlink synchronization establishment between the User Equipment(UE) and the base station. In particular, the uncertainty of the synchronization signals on the frequency domain and the flexibility of frame structure configuration have brought great challenges to the initial cell search for the fifth-generation(5G) new radio(NR). To solve this problem, firstly, we analyze the physical layer frame structure of 5G NR systems. Then, by focusing on the knowledge of synchronization signals, the 5G NR cell search process is designed, and the primary synchronization signal(PSS) timing synchronization algorithm is proposed, including a 5G-based coarse synchronization algorithm and conjugate symmetry-based fine synchronization algorithm. Finally, the performance of the proposed cell search algorithm in 5G NR systems is verified through the combination of Digital Signal Processing(DSP) and personal computer(PC). And the MATLAB simulation proves that the proposed algorithm has better performance than the conventional cross-correlation algorithm when a certain frequency offset exists.

Challenges for beyond 5G:ultra-densification of radio access network

Ultra-densification of radio access network(RAN)is a key to efficiently support the exponentially growing mobile data traffic in 5 G era.Furthermore,extremely high frequency band like mm Wave band was utilized to solve the bandwidth shortage problem.However,untra-dense reusing the same radio resource produced severe interference.And the mm Wave link was very harsh due to frequent blockage by obstacles.Therefore a new RAN architecture needed to be introduced to realize ultra-reliable communications in such a severe radio propagation environment.An architecture of distributed MIMO based RAN was presented.Then,enhanced interference coordination(e IC)was described.Finally,the effectiveness of distributed MIMO based RAN with e IC by computer simulation was showed.

On Design of Conjugated Transmission Scheme for FBMC/OQAM Systems with Interference Cancellation

Compared to OFDM systems with cyclic prefi x, fi lterbank multicarrier with offset quadrature amplitude modulation(FBMC/OQAM) system is considered as an alternative technology for next generation wireless communication systems. However, FBMC systems suffer from intrinsic imaginary interference caused by the real-fi eld orthogonality destruction when passing through complex-valued fading channels. By analyzing the transmultiplexer's response of FBMC/OQAM systems, in this paper, a simple conjugated transmission scheme is proposed for FBMC/OQAM systems. Following the specific conjugation design, the intrinsic imaginary interference including the intrinsic inter-symbol and the inter-carrier interference can be eliminated at the receiver side through linear signal processing operation. Meanwhile, the proposed conjugated transmission scheme is able to obtain extra linear combination diversity gains for improving the systematic performance of FBMC/OQAM. Simulation results show that the proposed scheme is more efficient than conventional methods, especially in practical application scenarios with large Doppler spread caused by high-speed movement.

Energy-efficiency based downlink multi-user hybrid beamforming for millimeter wave massive MIMO system

The fifth generation mobile communication（5G） systems can provide Gbit/s data rates from massive multiple-input multiple-output（MIMO） combined with the emerging use of millimeter wavelengths in small heterogeneous cells. This paper develops an energy-efficiency based multi-user hybrid beamforming for downlink millimeter wave（mm Wave） massive MIMO systems. To make better use of directivity gains of the analog beamforming and flexible baseband processing of the digital beamforming, this paper proposes the analog beamforming to select the optimal beam which can maximize the power of the objective user and minimize the interference to all other users. In addition, the digital beamforming maximizes the energy efficiency of the objective user with zero-gradient-based approach. Simulation results show the proposed algorithm provide better bit error rate（BER） performance compared with the traditional hybrid beamforming and obviously improved the sum rate with the increase in the number of users. It is proved that multi-user MIMO（MU-MIMO） can be a perfect candidate for mm Wave massive MIMO communication system. Furthermore, the analog beamforming can mitigate the inter-user interference more effectively with the selection of the optimal beam and the digital beamforming can greatly improve the system performance through flexible baseband processing.