Performance analysis of massive multiple input multiple output for high speed railway

This paper analytically reviews the performance of massive multiple input multiple output (MIMO) system for communication in highly mobility scenarios like high speed Railways. As popularity of high speed train increasing day by day, high data rate wireless communication system for high speed train is extremely required. 5G wireless communication systems must be designed to meet the requirement of high speed broadband services at speed of around 500 km/h, which is the expected speed achievable by HSR systems, at a data rate of 180 Mbps or higher. Significant challenges of high mobility communications are fast time-varying fading, channel estimation errors, doppler diversity, carrier frequency offset, inter carrier interference, high penetration loss and fast and frequent handovers. Therefore, crucial requirement to design high mobility communication channel models or systems prevails. Recently, massive MIMO techniques have been proposed to significantly improve the performance of wireless networks for upcoming 5G technology. Massive MIMO provide high throughput and high energy efficiency in wireless communication channel. In this paper, key findings, challenges and requirements to provide high speed wireless communication onboard the high speed train is pointed out after thorough literature review. In last, future research scope to bridge the research gap by designing efficient channel model by using massive MIMO and other optimization method is mentioned

OTFS-NOMA: An Efficient Approach for Exploiting Heterogenous User Mobility Profiles

This paper considers a challenging communication scenario, in which users have heterogenous mobility profiles, e.g., some users are moving at high speeds and some users are static. A new non-orthogonal multiple-access (NOMA) transmission protocol that incorporates orthogonal time frequency space (OTFS) modulation is proposed. Thereby, users with different mobility profiles are grouped together for the implementation of NOMA. The proposed OTFS-NOMA protocol is shown to be applicable to both uplink and downlink transmission, where sophisticated transmit and receive strategies are developed to remove inter-symbol interference and harvest both multi-path and multi-user diversity. Analytical results demonstrate that both the high-mobility and low-mobility users benefit from the application of OTFS-NOMA. In particular, the use of NOMA allows the spreading of the high-mobility users' signals over a large amount of time-frequency resources, which enhances the OTFS resolution and improves the detection reliability. In addition, OTFS-NOMA ensures that low-mobility users have access to bandwidth resources which in conventional OTFS-orthogonal multiple access (OTFS-NOMA) would be solely occupied by the high-mobility users. Thus, OTFS-NOMA improves the spectral efficiency and reduces latency

A Reduced Complexity Ungerboeck Receiver for Quantized Wideband Massive SC-MIMO

Employing low resolution analog-to-digital converters in massive multiple-input multiple-output (MIMO) has many advantages in terms of total power consumption, cost and feasibility of such systems. However, such advantages come together with significant challenges in channel estimation and data detection due to the severe quantization noise present. In this study, we propose a novel iterative receiver for quantized uplink single carrier MIMO (SC-MIMO) utilizing an efficient message passing algorithm based on the Bussgang decomposition and Ungerboeck factorization, which avoids the use of a complex whitening filter. A reduced state sequence estimator with bidirectional decision feedback is also derived, achieving remarkable complexity reduction compared to the existing receivers for quantized SC-MIMO in the literature, without any requirement on the sparsity of the transmission channel. Moreover, the linear minimum mean-square-error (LMMSE) channel estimator for SC-MIMO under frequency-selective channel, which do not require any cyclic-prefix overhead, is also derived. We observe that the proposed receiver has significant performance gains with respect to the existing receivers in the literature under imperfect channel state information.Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

Design and Performance Analysis of the Dynamic Reduction of Intrinsic Interference Suppression and BER using QAM-based FBMC for MU-MIMO Communications

The present research work is focused on the study of co-channel interface with its minimization techniques without influencing its performance, in turn, which is desired to achieve the minimized complexity of Quadrature Amplitude Modulation (QAM)-based Filter Bank Multi-Carrier (FBMC) to minimize the interference and increase the spectral features with consideration of intrinsic features extractions for the ML (Maximum Likelihood) synthesis systems. The valid measures are given various concerns under consideration, to start with the consideration of the evaluation of the Cyclic Prefix Orthogonal Frequency Division Multiplexing (CP-OFD performance metrics along with the FBMC/QAM in signal transmission in a dedicated fading channel for the evaluation of the modulation order and BER as a required trade-off for quality assessments. From the results, it can be noted that the proposed FBMC QAM has performed better when compared with conventional FBMC systems. The present research also includes considering and calculating the efficiency of nonlinear channels with the Multi-User Multiple Input Multiple Output (MU-MIMO) and FBMC/QAM techniques. In continuation, the obtained results are dominating significantly to access the possible solution to meet the efficiency of the proposed system. In the next part of the research, it is considered with implementation of the sub-detector during the downlink of the system with the technique of threshold-driven strategy for better accuracy and minimization of the complexity in terms of ML detection in terms of order of its modulation. The calculations of the proposed technique with better BER are done on the recent MATLAB platform with its simulation demonstration for its detailed observation

A Data-Aided Channel Estimation Scheme for Decoupled Systems in Heterogeneous Networks

Uplink/downlink (UL/DL) decoupling promises more flexible cell association and higher throughput in heterogeneous networks (HetNets), however, it hampers the acquisition of DL channel state information (CSI) in time-division-duplex (TDD) systems due to different base stations (BSs) connected in UL/DL. In this paper, we propose a novel data-aided (DA) channel estimation scheme to address this problem by utilizing decoded UL data to exploit CSI from received UL data signal in decoupled HetNets where a massive multiple-input multiple-output BS and dense small cell BSs are deployed. We analytically estimate BER performance of UL decoded data, which are used to derive an approximated normalized mean square error (NMSE) expression of the DA minimum mean square error (MMSE) estimator. Compared with the conventional least square (LS) and MMSE, it is shown that NMSE performances of all estimators are determined by their signal-to-noise ratio (SNR)-like terms and there is an increment consisting of UL data power, UL data length and BER values in the SNR-like term of DA method, which suggests DA method outperforms the conventional ones in any scenarios. Higher UL data power, longer UL data length and better BER performance lead to more accurate estimated channels with DA method. Numerical results verify that the analytical BER and NMSE results are close to the simulated ones and a remarkable gain in both NMSE and DL rate can be achieved by DA method in multiple scenarios with different modulations

Low complexity detection for SC-FDE massive MIMO systems

Nowadays we continue to observe a big and fast growth of wireless com-munication usage due to the increasing number of access points, and fields of application of this technology. Furthermore, these new usages can require higher speed and better quality of service in order to create market. As example we can have: live 4K video transmission, M2M (Machine to Machine communication), IoT (Internet of Things), Tactile Internet, between many others. As a consequence of all these factors, the spectrum is getting overloaded with communications, increasing the interference and affecting the system's per-formance. Therefore a different path of ideas has been followed and the commu-nication process has been taken to the next level in 5G by the usage of big arrays of antennas and multi-stream communication (MIMO systems) which in a greater scale are called massive MIMO schemes. These systems can be combined with an SC-FDE (Single-Carrier Frequency Domain Equalization) scheme to im-prove the power efficiency due to the low envelope fluctuations. This thesis focused on the equalization in massive MIMO systems, more specifically in the FDE (Frequency Domain Equalization), studying the perfor-mance of different approaches, namely ZF (Zero Forcing), EGD (Equal Gain De-tector), MRD (Maximum Ratio Detector), IB-DFE (Iterative Block Decision Feed-back Equalizer) and a proposed receiver combining MRD (or EGD) and IB-DFE.With this approach we want to minimize the ICI (Inter Carrier Interference) in order to have almost independent data streams and to produce a low complexity code, so that the receiver's performance doesn't affect the total system's perfor-mance, with a final objective of increasing the data throughput in a great scale