373 research outputs found
Low-complexity Location-aware Multi-user Massive MIMO Beamforming for High Speed Train Communications
Massive Multiple-input Multiple-output (MIMO) adaption is one of the primary
evolving objectives for the next generation high speed train (HST)
communication system. In this paper, we consider how to design an efficient
low-complexity location-aware beamforming for the multi-user (MU) massive MIMO
system in HST scenario. We first put forward a low-complexity beamforming based
on location information, where multiple users are considered. Then, without
considering inter-beam interference, a closed-form solution to maximize the
total service competence of base station (BS) is proposed in this MU HST
scenario. Finally, we present a location-aid searching-based suboptimal
solution to eliminate the inter-beam interference and maximize the BS service
competence. Various simulations are given to exhibit the advantages of our
proposed massive MIMO beamforming method.Comment: This paper has been accepted for future publication by VTC2017-Sprin
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
RIS-assisted Scheduling for High-Speed Railway Secure Communications
With the rapid development of high-speed railway systems and railway wireless
communication, the application of ultra-wideband millimeter wave band is an
inevitable trend. However, the millimeter wave channel has large propagation
loss and is easy to be blocked. Moreover, there are many problems such as
eavesdropping between the base station (BS) and the train. As an emerging
technology, reconfigurable intelligent surface (RIS) can achieve the effect of
passive beamforming by controlling the propagation of the incident
electromagnetic wave in the desired direction.We propose a RIS-assisted
scheduling scheme for scheduling interrupted transmission and improving quality
of service (QoS).In the propsed scheme, an RIS is deployed between the BS and
multiple mobile relays (MRs). By jointly optimizing the beamforming vector and
the discrete phase shift of the RIS, the constructive interference between
direct link signals and indirect link signals can be achieved, and the channel
capacity of eavesdroppers is guaranteed to be within a controllable range.
Finally, the purpose of maximizing the number of successfully scheduled tasks
and satisfying their QoS requirements can be practically realized. Extensive
simulations demonstrate that the proposed scheme has superior performance
regarding the number of completed tasks and the system secrecy capacity over
four baseline schemes in literature.Comment: 15 pages, 10 figures, to appear in IEEE Transactions on Vehicular
Technolog
Reconfigurable Intelligent Surface Assisted High-Speed Train Communications: Coverage Performance Analysis and Placement Optimization
Reconfigurable intelligent surface (RIS) emerges as an efficient and
promising technology for the next wireless generation networks and has
attracted a lot of attention owing to the capability of extending wireless
coverage by reflecting signals toward targeted receivers. In this paper, we
consider a RIS-assisted high-speed train (HST) communication system to enhance
wireless coverage and improve coverage probability. First, coverage performance
of the downlink single-input-single-output system is investigated, and the
closed-form expression of coverage probability is derived. Moreover, travel
distance maximization problem is formulated to facilitate RIS discrete phase
design and RIS placement optimization, which is subject to coverage probability
constraint. Simulation results validate that better coverage performance and
higher travel distance can be achieved with deployment of RIS. The impacts of
some key system parameters including transmission power, signal-to-noise ratio
threshold, number of RIS elements, number of RIS quantization bits, horizontal
distance between base station and RIS, and speed of HST on system performance
are investigated. In addition, it is found that RIS can well improve coverage
probability with limited power consumption for HST communications.Comment: 14 figures, accepted by IEEE Transactions on Vehicular Technolog
Contextual Beamforming: Exploiting Location and AI for Enhanced Wireless Telecommunication Performance
The pervasive nature of wireless telecommunication has made it the foundation
for mainstream technologies like automation, smart vehicles, virtual reality,
and unmanned aerial vehicles. As these technologies experience widespread
adoption in our daily lives, ensuring the reliable performance of cellular
networks in mobile scenarios has become a paramount challenge. Beamforming, an
integral component of modern mobile networks, enables spatial selectivity and
improves network quality. However, many beamforming techniques are iterative,
introducing unwanted latency to the system. In recent times, there has been a
growing interest in leveraging mobile users' location information to expedite
beamforming processes. This paper explores the concept of contextual
beamforming, discussing its advantages, disadvantages and implications.
Notably, the study presents an impressive 53% improvement in signal-to-noise
ratio (SNR) by implementing the adaptive beamforming (MRT) algorithm compared
to scenarios without beamforming. It further elucidates how MRT contributes to
contextual beamforming. The importance of localization in implementing
contextual beamforming is also examined. Additionally, the paper delves into
the use of artificial intelligence schemes, including machine learning and deep
learning, in implementing contextual beamforming techniques that leverage user
location information. Based on the comprehensive review, the results suggest
that the combination of MRT and Zero forcing (ZF) techniques, alongside deep
neural networks (DNN) employing Bayesian Optimization (BO), represents the most
promising approach for contextual beamforming. Furthermore, the study discusses
the future potential of programmable switches, such as Tofino, in enabling
location-aware beamforming
Performance investigation of spatial modulation systems under realistic channel models
In order to fulfil the explosive demand for convenient wireless data access, novel wireless technologies such as the multiple-input-multiple-output (MIMO) have widely been used to improve the link reliability and capacity of wireless communication systems. In recent years, a new MIMO technology named the spatial modulation (SM) has attracted signi cant research interest due to its reported enhancement on the system performance with the reasonable system complexity. Before a new technology comes into real use, it is necessary to comprehensively evaluate its performance under different scenarios. In this thesis, we investigate the performance of SM systems under some important realistic scenarios for future wireless communications, such as the vehicle-to-vehicle (V2V), the high-speed train (HST), and the massive MIMO scenarios. Firstly, the bit error rate (BER) performance of SM systems under a novel threedimensional (3D) geometry based stochastic model (GBSM) for V2V MIMO channels is investigated by both theoretical analysis and system simulations. The impacts of vehicle tra c density (VTD), Doppler effect, and 3D feature on the BER performance of SM systems are thoroughly studied. In addition, other MIMO technologies, such as the vertical Bell Labs layered space-time (V-BLAST), the Alamouti scheme are compared with SM under different simulation settings. Secondly, the BER performance of SM systems is studied under a non-stationary wideband HST GBSM considering the non-ideal channel estimation case. The timevarying behaviour of the channel and its impact on the performance of SM systems are comprehensively investigated. The accurate theoretical BER expression of SM systems under a non-stationary wideband HST channels with non-ideal channel estimation is derived. A novel statistic property named stationary interval in terms of the space-time correlation function (STCF) is introduced in order to clearly explain all theoretical and simulation results. Thirdly, the performance of SM systems is evaluated under a Kroneck-based massive MIMO channel model. As a massive MIMO system employs large numbers of antennas, antenna elements are distributed over a wide range. Thus, different antenna elements may observe different sets of clusters. How this phenomenon affects the performance of SM systems is investigated by considering a survival probability of clusters, which abstracts the birth-death process of each cluster in the channel model. Moreover, the performance of SM systems is also compared with that of other MIMO technologies under the massive MIMO channel model. In summary, all research works in this thesis have considered realistic MIMO channel models, which are meaningful for the test, performance evaluation, and implementation of SM technology for future advanced wireless communications systems
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