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Showing papers by "NTT DoCoMo published in 2019"


Journal ArticleDOI
TL;DR: A variational optimization problem to improve the reliability of grant-free NOMA is formulated by parameterizing the intractable variational function with a specially designed deep neural network, which incorporates random user activation and symbol spreading.
Abstract: Tactile Internet of Things (IoT) requires ultraresponsive and ultrareliable connections for massive IoT devices. As a promising enabler of tactile IoT, grant-free nonorthogonal multiple access (NOMA) exploits the joint benefit of grant-free access and nonorthogonal transmissions to achieve low latency massive access. However, it suffers from the reduced reliability caused by random interference. Hence, we formulate a variational optimization problem to improve the reliability of grant-free NOMA. Due to the intractability of this problem, we resort to deep learning by parameterizing the intractable variational function with a specially designed deep neural network, which incorporates random user activation and symbol spreading. The network is trained according to a novel multiloss function where a confidence penalty based on the user activation probability is considered. The spreading signatures are automatically generated while training, which matches the highly automatic applications in tactile IoT. The significant reliability gain of our scheme is validated by simulations.

109 citations


Journal ArticleDOI
TL;DR: In this paper, the authors considered a scenario where UAV-BSs are serving a large number of mobile users in a hot spot area (e.g., in a stadium).
Abstract: Unmanned aerial vehicle (UAV) base stations (BSs) can be a promising solution to provide connectivity and quality-of-service guarantees during temporary events and after disasters. In this paper, we consider a scenario where UAV-BSs are serving a large number of mobile users in a hot spot area (e.g., in a stadium). We introduce non-orthogonal multiple-access (NOMA) transmission at UAV-BSs to serve more users simultaneously considering user distances as the available feedback for a user ordering during NOMA formulation. With millimeter-wave transmission and multi-antenna techniques, we assume that UAV-BS generates directional beams and multiple users are served simultaneously within the same beam. However, due to the limitations of physical vertical beamwidth of the UAV-BS beam, it may not be possible to cover the entire user region at UAV altitudes of practical relevance. During such situations, a beam scanning approach is proposed to maximize the achievable sum rates. We develop a comprehensive framework over which outage probabilities and respective sum rates are derived rigorously and we investigate the optimal operational altitude of UAV-BS to maximize the sum rates using our analytical framework. Our analysis shows that NOMA with distance feedback can provide better outage sum rates than orthogonal multiple access.

47 citations


Proceedings Article
01 Mar 2019
TL;DR: This paper explains the proposed radio propagation prediction model using convolutional neural networks by deep learning in detail, and clarifies its performance by evaluating behaviors for map-parameters input to CNN.
Abstract: Recently, advancement of artificial intelligence has been remarkable, and many applied researches are attracting attention now. Most of them are based on deep learning. Here, we have proposed radio propagation prediction model using convolutional neural networks (CNN) by deep learning. This paper explains our proposed model in detail, and clarifies its performance by evaluating behaviors for map-parameters input to CNN.

38 citations


Journal ArticleDOI
TL;DR: The blending end-to-end trainable models associated to meaningful prior knowledge performs the best for the restaurant retrieval for Track 1 and Hybrid Code Network and Memory Network have been the best models for this task.

38 citations


Journal ArticleDOI
TL;DR: In this article, the authors consider an UAV-based wireless network using non-orthogonal multiple access (NOMA) transmission in millimeter-wave frequencies to deliver broadband data in a spectrally efficient fashion at hotspot scenarios.
Abstract: In this paper, we consider an unmanned aerial vehicle (UAV) based wireless network using non-orthogonal multiple access (NOMA) transmission in millimeter-wave frequencies to deliver broadband data in a spectrally efficient fashion at hotspot scenarios. The necessity for the NOMA transmitter to gather information on user channel quality becomes a major drawback in practical deployments. We therefore consider various limited feedback schemes for NOMA transmission, to relieve the complexity of tracking and feeding back the full channel state information (CSI) of the users. In particular, through beamforming we allow NOMA to exploit the space domain, and hence, the user angle emerges as a promising (yet novel) limited feedback scheme. We show that as the user region for NOMA transmission gets wider, the users become more distinctive at the transmitter side with respect to their angles, making user angle feedback a better alternative than distance feedback in such scenarios. We rigorously derive and analyze the outage sum rate performance for NOMA transmission considering various user ordering strategies involving full CSI, angle, and distance feedback schemes. Our analytical results for NOMA outage sum rates using those feedback schemes match closely with simulations, and provide useful insights on properly choosing a limited feedback scheme for different deployment geometries and operating configurations.

38 citations


Journal ArticleDOI
TL;DR: The T-shirt-type wearable ECG monitoring system was suitable for continuous, daily long-term use among young people with high physical activity, and it had the distinct capability of identifying covert AF.
Abstract: Covert atrial fibrillation (AF) accounts for cryptogenic stroke aetiology in elderly patients and in younger populations. However, asymptomatic AF is difficult to diagnose based on a short electrocardiography (ECG) recording. We evaluated the feasibility of a self-applied continuous ECG monitoring device that can record automatically, easily, and noninvasively in a younger population. We investigated community screening for asymptomatic AF using a wireless single-lead ECG with an electrode embedded in a T-shirt. One hundred men with a CHADS2 score ≥1 who were free from AF and 30 seconds was detected in 10 participants (10.0%). AF continuing for >6 minutes was detected in 2 participants (2.0%). The T-shirt-type wearable ECG monitoring system was suitable for continuous, daily long-term use among young people with high physical activity, and it had the distinct capability of identifying covert AF.

33 citations


Patent
30 May 2019
TL;DR: In this article, a radio communication system with a state management unit that manages a communication state of the user equipment and a state transition unit that causes it to transition from a connected state to a sustained state is described.
Abstract: An aspect of the present invention relates to a radio communication system, including: a user equipment, wherein the user equipment includes a state management unit that manages a communication state of the user equipment, and a state transition unit that causes the communication state of the user equipment to transition, and when a sustenance message for causing the user equipment to transition from a connected state to a sustained state is received from a first base station, the state transition unit causes the user equipment to transition from the connected state to the sustained state, and the state management unit extracts a context identifier specifying radio parameter information for radio communication between the user equipment and the first base station and a base station-based location registration area configured with one or more cells including a cell of the first base station from the sustenance message and retains the radio parameter information, the context identifier, and the base station-based location registration area.

24 citations


Journal ArticleDOI
TL;DR: In this article, the authors proposed a fog massive multi-in-multi-out (MIMO) architecture, where the user equipment (UE) nodes can connect to a "fog" of the densely deployed remote radio heads (RRHs) in a seamless, user-centric, and opportunistic manner.
Abstract: The decoupling of data and control planes in the forthcoming 5G wireless networks enables the efficient implementation of multitier architectures, where coverage and connectivity are guaranteed by top-tier macro-cells, and at the same time, high throughput and low latency are achieved locally by lower tiers in the hierarchy. This paper considers a new architecture for such lower tiers, dubbed fog massive multi-in multi-out (MIMO), where the user equipment (UE) nodes can connect to a “fog” of the densely deployed remote radio heads (RRHs) in a seamless, user-centric, and opportunistic manner. In the case of dense small cells, traditional cellular architectures inherently give rise to frequent handovers and pilot sequence re-assignments, which typically incur excessive protocol overhead and latency. In the proposed fog massive MIMO architecture, the UEs implicitly associate themselves with the most convenient RRHs in a completely autonomous manner. Each UE makes use of the uplink pilot sequences that contain equal-weight codewords and enable a novel “on-the-fly” pilot contamination control mechanism. We analyze the spectral efficiency and the outage probability of the proposed architecture via stochastic geometry, using some recent results on unique coverage in Boolean models, and provide a detailed comparison with the benchmark represented by massive MIMO cellular system with a genie-aided minimum-distance user-cell association. Our analysis, corroborated by extensive system simulation, reveals that there exists a “sweet spot” of the per pilot user load (number of users per pilot), such that the proposed system achieves a spectral efficiency close to that of the genie-aided cellular system. In these conditions, it is possible to achieve the low protocol overhead and low user RRH association latency promised by the fog massive MIMO at virtually no significant performance cost in terms of system spectral efficiency with respect to the cellular benchmark.

23 citations


Proceedings ArticleDOI
01 Jan 2019
TL;DR: Results show that using a 33 inch by 33 inch metallic reflector, the received power can be enhanced by 19 dB compared to no reflector case, and the strong link quality by a large margin to line-of-sight (LOS) links.
Abstract: The availability of large unused spectrum at millimeter wave (mmWave) frequency bands has steered the future 5G research towards these bands. However, mmWave signals are attenuated severely in the non-line-of-sight (NLOS) scenarios, thereby leaving the strong link quality by a large margin to line-of-sight (LOS) links. In this paper, a passive metallic reflector is used to enhance the coverage for mmWave signals in an outdoor, NLOS propagation scenarios. The received power from different azimuth and elevation angles are measured at 28 GHz in a parking lot setting. Our results show that using a 33 inch by 33 inch metallic reflector, the received power can be enhanced by 19 dB compared to no reflector case.

22 citations


Proceedings ArticleDOI
02 May 2019
TL;DR: ZeRONE is a helium blimp type drone that uses the wind generated by the ultrasonic vibration of piezo elements for propulsion that is much safer because its only moving parts are thePiezo elements whose surfaces vibrate at the order of micrometers.
Abstract: We present ZeRONE, a new indoor drone that does not use rotating blades for propulsion. The proposed device is a helium blimp type drone that uses the wind generated by the ultrasonic vibration of piezo elements for propulsion. Compared to normal drones with rotating propellers, the drone is much safer because its only moving parts are the piezo elements whose surfaces vibrate at the order of micrometers. The drone can float for a few weeks and the ultrasonic propulsion system is quiet. We implement a prototype of the drone and evaluate its performance and unique characteristics in experiments. Moreover, application scenarios in which ZeRONE coexists with people are also discussed.

18 citations


Journal ArticleDOI
TL;DR: Recent activities on 5G transmission experiments that aim to validate Massive MIMO technologies using higher frequency bands such as SHF/EHF bands, that is, 5G experimental trials are introduced.
Abstract: In order to cope with recent growth of mobile data traffic and emerging various services, world-wide system trials for the fifthgeneration (5G) mobile communication system that dramatically extends capability of the fourth-generation mobile communication system are being performed to launch its commercial service in 2020. In addition, research and development of new radio access technologies for 5G evolution and beyond 5G systems are beginning to be made all over the world. This paper introduces our recent activities on 5G transmission experiments that aim to validate Massive MIMO technologies using higher frequency bands such as SHF/EHF bands, that is, 5G experimental trials. Recent results of 5G system trials to create new services and applications in 5G era in cooperation with partners in vertical industries are also introduced. key words: fifth generation mobile communication system, radio access technology, higher frequency band, experimental trial, system trial

Proceedings Article
01 Jan 2019
TL;DR: This work presents a methodology to build domain specific KG by merging output from deep learning-based relation extraction from free text and existing knowledge database such as Wikidata, satisfying the requirement of specific knowledge-oriented AI tasks such as question answering, chatting, or intelligent retrieval.
Abstract: Many AI agent tasks require domain specific knowledge graph (KG) that is compact and complete. We present a methodology to build domain specific KG by merging output from deep learning-based relation extraction from free text and existing knowledge database such as Wikidata. We first form a static KG by traversing knowledge database constrained by domain keywords. Very large high-quality training data set is then generated automatically by matching Common Crawl data with relation keywords extracted from knowledge database. We describe the training data generation process in detail and subsequent experiments with deep learning approaches to relation extraction. The resulting model is used to generate new triples from free text corpus and create a dynamic KG. The static and dynamic KGs are then merged into a new KB satisfying the requirement of specific knowledge-oriented AI tasks such as question answering, chatting, or intelligent retrieval. The proposed methodology can be easily transferred to other domains or languages.

Journal ArticleDOI
TL;DR: This paper proposes an extensive game-based algorithm aiming at strengthening the security of both cellular and the D2D communications via system resource allocation, and shows that the proposed method is able to efficiently improve the overall system security when compared to existing studies.
Abstract: Device-to-device (D2D) communication has been increasingly attractive due to its great potential to improve cellular communication performance. While resource allocation optimization for improving the spectrum efficiency is of interest in the D2D-related work, communication security, as a key issue in the system design, has not been well investigated yet. Recently, a few studies have shown that D2D users can actually serve as friendly jammers to help enhance the security of cellular user communication against eavesdropping attacks. However, only a few studies considered the security of D2D communications. In this paper, we consider the secure resource allocation problem, particularly, how to assign resources to cellular and the D2D users to maximize the system security. To solve this problem, we propose an extensive game-based algorithm aiming at strengthening the security of both cellular and the D2D communications via system resource allocation. Finally, the simulation results show that the proposed method is able to efficiently improve the overall system security when compared to existing studies.

Proceedings ArticleDOI
01 Apr 2019
TL;DR: The trial results prove that coverage ratio is significant improved with deploying IAB node, and user throughput gain is obvious due to better resource utilization and providing more access transmission opportunities for User Equipment (UE) in backhaul slot.
Abstract: Higher bandwidth and spatial reuse through densification of wireless cells are necessary to meet the increase of wireless traffic demand in the next decade. Millimeter wave network can fulfill both of these criteria with the availability of abundant bandwidth and higher spatial reuse through directional beamforming. However, millimeter wave network suffers from coverage hole in urban environment due to blockage because of high path loss for millimeter wave signals. Wireless backhaul allows densification of mobile networks without incurring additional fiber deployment cost. Millimeter wave band based Integrated access and backhaul (IAB) is expected to provide a low cost coverage enhancement and capacity improvement solution. This paper focuses on the system performance of IAB node deployment in terms of coverage and user throughput by field experiment using millimeter wave band. The trial results prove that coverage ratio is significant improved with deploying IAB node. Meanwhile, dynamic resource allocation, including dynamic time division multiplexing (TDM) and dynamic TDM with flexible space division multiplexing (SDM) between access and backhaul link, brings obvious user throughput gain due to better resource utilization and providing more access transmission opportunities for User Equipment (UE) in backhaul slot.

Patent
Yasukawa Shimpei1, Satoshi Nagata1, Zhao Qun, Liu Liu, Anxin Li, Huiling Jiang 
02 Apr 2019
TL;DR: In this paper, the user equipment includes a detection unit that detects, by performing sensing in a time window for sensing, one or more resources capable of transmitting a signal, and a selection unit that selects a signal from the detected resources; and a transmission unit that transmits the signal using the selected resource for transmitting the signal.
Abstract: There is provided user equipment that selects a resource for transmitting a signal based on a sensing result. The user equipment includes a detection unit that detects, by performing sensing in a time window for sensing, one or more resources capable of transmitting a signal in a time window for resource selection after the time window for sensing; a selection unit that selects a resource for transmitting a signal from the one or more detected resources; and a transmission unit that transmits the signal using the selected resource for transmitting the signal.

Patent
07 Mar 2019
TL;DR: In this paper, a method and apparatus for base station selection based on uplink pilot and distributed user-proximity detection is presented. In one embodiment, the method comprises performing uplink helicopter pilot configuration for a plurality of user terminals over a set of common resource elements, including generating a plurality pattern for each different one of the user terminals has a different position in the pilot pattern.
Abstract: A method and apparatus is disclosed herein for base station selection based on uplink pilot and distributed user-proximity detection. In one embodiment, the method comprises performing uplink pilot configuration for a plurality of user terminals over a set of common resource elements, including generating a plurality of pilot patterns for the plurality of user terminals, where each of the plurality of pilot patterns comprises at least one zero-power resource element and at least one non-zero-power resource element and at least one zero-power resource element allocated to each different one of the plurality of user terminals has a different position in the pilot pattern.

Proceedings ArticleDOI
05 Nov 2019
TL;DR: This paper proposes a method to predicting bike demand and the number of bike pickups and drop offs at each bike-port every hour, up to 24 hours in advance, based on the Variational Autoencoders model and the Attention based Sequence to Sequence learning model.
Abstract: In recent years, bicycle sharing services (bike-shares) have been established worldwide. One important aspect of bike-share management is to periodically rebalance the positions of the available bikes. Because the bike demand varies by and over time, the number of bikes at each bike-port tends to become unbalanced. To efficiently rebalance a bike-share system, it is essential to predicting the number of bikes in each bike-port. In this paper, we propose a method to predicting bike demand and the number of bike pickups and drop offs at each bike-port every hour, up to 24 hours in advance. To predict demand, we used a time series generation model based on the Variational Autoencoders model and the Attention based Sequence to Sequence learning model. We named this method "Conditional Variational Autoencoders considering Partial Future data" (CVAE-PF). In the experiment, our proposed method showed higher prediction accuracy in root mean square error (RMSE) compared to conventional methods.

Journal ArticleDOI
01 Feb 2019-BMJ Open
TL;DR: The Maternity Log study was designed to construct a time-course high-resolution reference catalogue of bioinformatic data in pregnancy and explore the associations between genomic and environmental factors and the onset of pregnancy complications, using continuous lifestyle monitoring combined with multiomics data on the genome, transcriptome, proteome, metabolome and microbiome.
Abstract: Purpose A prospective cohort study for pregnant women, the Maternity Log study, was designed to construct a time-course high-resolution reference catalogue of bioinformatic data in pregnancy and explore the associations between genomic and environmental factors and the onset of pregnancy complications, such as hypertensive disorders of pregnancy, gestational diabetes mellitus and preterm labour, using continuous lifestyle monitoring combined with multiomics data on the genome, transcriptome, proteome, metabolome and microbiome. Participants Pregnant women were recruited at the timing of first routine antenatal visits at Tohoku University Hospital, Sendai, Japan, between September 2015 and November 2016. Of the eligible women who were invited, 65.4% agreed to participate, and a total of 302 women were enrolled. The inclusion criteria were age ≥20 years and the ability to access the internet using a smartphone in the Japanese language. Findings to date Study participants uploaded daily general health information including quality of sleep, condition of bowel movements and the presence of nausea, pain and uterine contractions. Participants also collected physiological data, such as body weight, blood pressure, heart rate and body temperature, using multiple home healthcare devices. The mean upload rate for each lifelog item was ranging from 67.4% (fetal movement) to 85.3% (physical activity), and the total number of data points was over 6 million. Biospecimens, including maternal plasma, serum, urine, saliva, dental plaque and cord blood, were collected for multiomics analysis. Future plans Lifelog and multiomics data will be used to construct a time-course high-resolution reference catalogue of pregnancy. The reference catalogue will allow us to discover relationships among multidimensional phenotypes and novel risk markers in pregnancy for the future personalised early prediction of pregnancy complications.

Proceedings ArticleDOI
01 Dec 2019
TL;DR: In this paper, the effectiveness of the metasurface reflectors in expanding 5G coverage into non-line-of-sight (NLoS) regions in the 28 GHz frequency band is evaluated.
Abstract: We experimentally verify the effectiveness of metasurface reflectors in expanding 5G coverage into non-line-of sight (NLoS) regions in the 28-GHz frequency band. In outdoor open space measurements, the measured beam shape is well matched with that designed with an 18-degree beamwidth. Improvements in the beam-reference-signal received power (BRSRP) and downlink (DL) throughput of approximately 15 dB and 100%, respectively, are observed over a 35-m range in a NLoS area in a real urban environment. Consequently, the effectiveness of the metasurface reflectors in expanding 5G coverage into the NLoS region are experimentally verified in a real urban environment using a 5G testbed system.

Proceedings ArticleDOI
20 May 2019
TL;DR: As the simulations reveal, NN-based location estimators trained with user-sector channel gains could be a viable approach for providing user location information at the network side, linear regression, weighted K-nearest neighbors (WKNN), and neural networks (NN) are evaluated.
Abstract: Gains in area spectral efficiency have been recently demonstrated in networks of large-antenna arrays by means of fog massive MIMO operation and virtual sector-based processing. In this paper, we adopt such sector-based processing and operation to localize users in the network. We investigate the viability of some widely used supervised-learning methods in estimating user locations by observing across the fog massive MIMO network signals transmitted by the users. In particular, we evaluate linear regression (LR), weighted K-nearest neighbors (WKNN), and neural networks (NN) in the context of a network of massive-antenna remote-radio heads (RRHs) using simulations based on a spatially consistent channel model. As our simulations reveal, NN-based location estimators trained with user-sector channel gains could be a viable approach for providing user location information at the network side.

Proceedings ArticleDOI
01 Apr 2019
TL;DR: A cluster-based resource selection scheme is proposed to reduce the resource collision, where resources are divided into different resource sets and each cluster head selects its available resource set based on measurement.
Abstract: The vehicle to everything communication in long term evolution (LTE V2X) supports vehicle-to-vehicle (V2V) communication directly via PC5 interface. In LTE V2X mode 4, vehicles autonomously select radio resources based on a distributed scheduling scheme. However, some researches show that this sensing based semi-persistent scheduling (SPS) scheme incurs low transmission reliability due to resource contention especially when the transmissions are aperiodic. Therefore, a cluster-based resource selection scheme is proposed to reduce the resource collision, where resources are divided into different resource sets and each cluster head selects its available resource set based on measurement. Simulation results show that, compared with LTE V2X mode 4, the proposed scheme has better performance for both periodic and aperiodic traffic.

Journal ArticleDOI
TL;DR: This paper introduces the position information to machine reading comprehension and investigates the performance of the positionInformation and demonstrates the effectiveness of position information by experimenting on TriviaQA dataset.
Abstract: When people do the reading comprehension, they often try to find the words from the passages which are similar to the question words first. Then people deduce the answer based on the context around these similar words. Therefore, the position information may be helpful in finding the answer rapidly and is useful for reading comprehension. However, previous attention-based machine reading comprehension models typically focus on the interaction between the question and the context representation without considering the position information. In this paper, we introduce the position information to machine reading comprehension and investigate the performance of the position information. The position information is experimented in three different ways: 1) position encoder; 2) attention mechanism; and 3) position mapping embedding. By experimenting on TriviaQA dataset, we have demonstrated the effectiveness of position information.

Proceedings ArticleDOI
Keiichi Ochiai1, Kohei Senkawa1, Naoki Yamamoto1, Yuya Tanaka1, Yusuke Fukazawa1 
25 Jul 2019
TL;DR: This work designs and implements a system that based on the user's smartphone activity detects that the user has a problem and requires help and helps with the troubleshooting by recommending possible solutions to the identified problem.
Abstract: Billions of people are using smartphones everyday and they often face problems and troubles with both the hardware as well as the software. Such problems lead to frustrated users and low customer satisfaction. Developing an automatic machine learning-based solution that would detect that the user has a problem and would engage in troubleshooting has the potential to significantly improve customer satisfaction and retention. Here, we design and implement a system that based on the user's smartphone activity detects that the user has a problem and requires help. Our system automatically detects a user has a problem and then helps with the troubleshooting by recommending possible solutions to the identified problem. We train our system based on large-scale customer support center data and show that it can both detect that a user has a problem as well as predict the category of the problem (89.7% accuracy) and quickly provide a solution (in 10.4ms). Our system has been deployed in commercial service since January, 2019. Online evaluation result showed that machine learning based approach outperforms the existing method by approximately 30% regarding the user problem solving rate.

Proceedings ArticleDOI
Rui Wang1, Hengtao He1, Shi Jin1, Xin Wang2, Xiaolin Hou2 
02 Jul 2019
TL;DR: An advanced channel estimation method based on generalized expectation consistent signal recovery (GEC-SR) algorithm, which can obtain accurate channel state information from quantized signal, and can reduce the required pilot overhead significantly by using orthogonal pilot.
Abstract: Channel estimation is very challenging for millimeter wave (mmWave) massive multiple input multiple output (MIMO) systems with low-resolution analog-to-digital converters (ADCs) owing to the severe nonlinear distortion introduced by quantization. In this paper, we develop an advanced channel estimation method based on generalized expectation consistent signal recovery (GEC-SR) algorithm, which can obtain accurate channel state information from quantized signal. Specifically, we consider Laplacian prior to model angular domain mmWave channel coefficients and embed the expectation-maximization (EM) principle into GEC-SR algorithm to learn the unknown prior parameters. Numerical results show that our method outperforms state-of-the-art generalized-approximate-message-passing-based channel estimator, and can reduce the required pilot overhead significantly by using orthogonal pilot.


Patent
02 Apr 2019
TL;DR: In this paper, a slice management device assigns a slice to a service in accordance with the context information such as a staying status or the like of the UE 130, and accordingly, a slice assigned to the service can be dynamically changed.
Abstract: A storage request accepting unit 11 acquires correspondence information in which a service, a slice, and context information are associated with each other A status acquiring unit 13 acquires positional information of a UE 130 and identifies staying information from the positional information An assignment unit 14 assigns a slice corresponding to a service used by the UE 130 and context information represented by the correspondence information In this case, a slice management device 10 assigns a slice to a service in accordance with the context information such as a staying status or the like of the UE 130, and accordingly, a slice assigned to the service can be dynamically changed

Proceedings ArticleDOI
01 Aug 2019
TL;DR: Computer simulation results show that among the three methods, the method in which the ideal peak reduction vector is projected onto the null space in the MIMO channel to generate a directional vector in the PC signal achieves the best PAPR reduction performance for a given computational complexity.
Abstract: In this paper, we investigate efficient methods for generating peak cancellation (PC) signals in a complexity-reduced algorithm for a peak-to-average power ration (PAPR) reduction method using the null space in a multiple-input multiple-output (MIMO) channel for MIMO-orthogonal frequency division multiplexing (OFDM) signals. The complexity-reduced algorithm performs vector-level signal processing in the PC signal in addition to the transmission signal at each transmitter antenna so that the PC signal is transmitted only to the null space in the MIMO channel. In this paper, we propose three methods to control the directional vector in the PC signal, which is a dominant factor in the achievable PAPR performance of the algorithm. Computer simulation results show that among the three methods, the method in which the ideal peak reduction vector is projected onto the null space in the MIMO channel to generate a directional vector in the PC signal achieves the best PAPR reduction performance for a given computational complexity.

Patent
Jing Wang1, Liu Liu1, Huiling Jiang, Takeda Fred, Nagata Satoshi 
21 Jun 2019
TL;DR: In this article, a beam determination method, a downlink transmission decoding method performed in a communication system, and corresponding user equipments and base stations are disclosed, where the base station has a plurality of transmission beams, and may dynamically select a beam for transmitting downlink control information and downlink data information.
Abstract: A beam determination method, a downlink transmission decoding method performed in a communication system, and corresponding user equipments and base stations are disclosed. The base station has a plurality of transmission beams, and may dynamically select a beam for transmitting downlink control information and downlink data information from a plurality of beams. The downlink transmission decoding method performed by the user equipment includes: determining M preferred beams in the plurality of transmission beams of the base station; and receiving, through one or more reception beams corresponding to any one or more of N preferred beams in the M preferred beams, downlink control information transmitted by the base station, wherein N≤M, the base station transmitting signaling including same downlink control information through the N preferred beams during the transmission time period of the downlink control information. The downlink transmission decoding method performed by the base station comprises: determining M preferred beams in the plurality of transmission beams of the base station; and transmitting signaling including same downlink control information through N preferred beams in the M preferred beams, where N≤M.

Book ChapterDOI
01 Jan 2019
TL;DR: This chapter focuses on downlink NOMA and its combination with open-loop SU-MIMO and assess its performance under realistic conditions and introduces the results of the experimental trials conducted.
Abstract: Non-orthogonal multiple access (NOMA) is a novel multi-user multiplexing scheme, which overlaps the radio resources of multiple users in an non-orthogonal manner in order to improve spectral efficiency. NOMA is able to contribute to the improvement of the trade-off between system capacity and user fairness by assigning different power ratios to the multiplexed users depending on their relative channel quality. In this chapter, we focus on downlink NOMA and its combination with open-loop SU-MIMO and assess its performance under realistic conditions. In particular, we introduce the results of the experimental trials we conducted in both indoor and outdoor environments using two users served by 2 \(\times \) 2 open-loop single-user (SU)-MIMO.

Patent
20 Jun 2019
TL;DR: In this article, a radio communication system consisting of a first data generation unit, a second data generator unit, and a transmission parameter determination unit is defined for the first data and a second transmission parameter for the second data.
Abstract: A radio communication apparatus functioning as a transmitter in a radio communication system including the transmitter and a receiver includes a first data generation unit that generates first data which are to be transmitted in accordance with a first transmission scheme, a second data generation unit that generates second data which are to be transmitted in accordance with a second transmission scheme, a transmission parameter determination unit that determines a first transmission parameter for the first data and a second transmission parameter for the second data, and a transmission unit that, when the second data are generated during transmission of the first data, punctures a portion of a resource allocated for the transmission of the first data, transmits the first data using the first transmission parameter in an unpunctured portion, and transmits the second data using the second transmission parameter in the punctured portion