Institution
NTT DoCoMo
About: NTT DoCoMo is a based out in . It is known for research contribution in the topics: Base station & Mobile station. The organization has 4032 authors who have published 8655 publications receiving 160533 citations.
Topics: Base station, Mobile station, Transmission (telecommunications), Signal, Terminal (electronics)
Papers published on a yearly basis
Papers
More filters
••
27 Jun 2016
TL;DR: The landscape of 5G use cases is analyzed and METIS-II 5GUse cases that cover the main 5G services, have stringent requirements and whose technical solutions are expected to serve other similar use cases as well are presented.
Abstract: One of the objectives of METIS-II project is to facilitate discussion on scenarios, use cases, KPIs and requirements for 5G, building upon the comprehensive work conducted in the METIS-I project and taking the work of other European projects as well as other bodies such as ITU-R, NGMN, etc. into account. This paper analyses the landscape of 5G use cases and presents METIS-II 5G use cases that cover the main 5G services, have stringent requirements and whose technical solutions are expected to serve other similar use cases as well. It also links these use cases to the business cases defined by 5G PPP so that requirements of vertical industries can be taken into account when designing the 5G Radio Access Network (RAN).
81 citations
••
TL;DR: This work briefly overviews the most promising TDD and FDD operation modes for massive MIMO, and discusses their potential benefits and challenges considering operation over different tiers and frequency bands.
Abstract: Massive MIMO is widely recognized as an essential technology for 5G. Together with newly allocated spectrum (bandwidth) and network densification (small cells), it is expected to play a key role in coping with the ongoing explosion in data-traffic demand and services. Compared to 4G MIMO technologies, massive MIMO can offer large gains in cell spectral efficiency, which, in combination with small cells and additional bandwidth, can translate into vast gains in throughput per unit area. We briefly overview the most promising TDD and FDD operation modes for massive MIMO, and discuss their potential benefits and challenges considering operation over different tiers and frequency bands. TDD operation is naturally suited to massive MIMO and can offer “massive MIMO” gains, with simple in-cell processing, low overheads and low end-to-end latencies. We also briefly describe some important massive MIMO activities towards 5G, including standardization efforts, system development and experimental trials. key words: 5G, massive MIMO, TDD, FDD
81 citations
••
TL;DR: A survey of transport methods for 3D video ranging from early analog 3D TV systems to most recent digital technologies that show promise in designing 3DTV systems of tomorrow focuses on the ubiquitous Internet as the network infrastructure of choice for future 3D television systems.
Abstract: We present a survey of transport methods for 3-D video ranging from early analog 3DTV systems to most recent digital technologies that show promise in designing 3DTV systems of tomorrow. Potential digital transport architectures for 3DTV include the DVB architecture for broadcast and the Internet Protocol (IP) architecture for wired or wireless streaming. There are different multiview representation/compression methods for delivering the 3-D experience, which provide a tradeoff between compression efficiency, random access to views, and ease of rate adaptation, including the "video-plus-depth" compressed representation and various multiview video coding (MVC) options. Commercial activities using these representations in broadcast and IP streaming have emerged, and successful transport of such data has been reported. Motivated by the growing impact of the Internet protocol based media transport technologies, we focus on the ubiquitous Internet as the network infrastructure of choice for future 3DTV systems. Current research issues in unicast and multicast mode multiview video streaming include network protocols such as DCCP and peer-to-peer protocols, effective congestion control, packet loss protection and concealment, video rate adaptation, and network/service scalability. Examples of end-to-end systems for multiview video streaming have been provided.
80 citations
••
01 Dec 2011TL;DR: The IRC receiver employing the covariance matrix comprising the interference and noise component estimation improves the cell-edge user throughput by approximately 22% compared to the simplified MMSE receiver that approximates the inter-cell interference as AWGN, while the IRC receiver employs the full covariance Matrix estimation degrades the average user throughput due to less accurate channel and covariance matrices.
Abstract: The interference rejection combining (IRC) receiver is effective in improving the cell-edge user throughput because it suppresses inter-cell interference. The IRC receiver is typically based on the minimum mean square error (MMSE) criteria, which requires channel estimation and covariance matrix estimation including the inter-cell interference with high accuracy. The paper investigates the gain from the IRC receiver taking into account the estimation of the interference signal, i.e., the covariance matrix, in terms of the downlink user throughput performance in a multi-cell environment. For the estimation of the covariance matrix, two estimation schemes are considered one based on data signals and the other based on the demodulation reference signal (DM-RS). In the evaluation, to assess the actual gains of the two schemes, the inter-cell interference signals from the surrounding 56 cells are actually generated in the same way as the desired signals including reference signals, and the channel propagation from all of the cells is explicitly taken into account considering pathloss, shadowing, and multipath fading. The simulation results when the inter-site distance is 500 m and the numbers of transmitter and receiver antennas are 2 and 2, respectively, show that the IRC receiver employing the covariance matrix comprising the interference and noise component estimation improves the cell-edge user throughput (defined as the 5% value in the cumulative distribution function) by approximately 22% compared to the simplified MMSE receiver that approximates the inter-cell interference as AWGN, while the IRC receiver employing the full covariance matrix estimation degrades the average user throughput due to less accurate channel and covariance matrices.
80 citations
•
14 Mar 2008TL;DR: In this paper, a base station apparatus used in a mobile communication system where user terminals with various numbers of reception antennas may be situated includes a providing unit configured to provide plural reference signals according to the number of transmission antennas; a precoding unit that replicates each of a predetermined number of input signal sequences according to a number of transmitted antennas, apply a predetermined precoding vector to each of the replicated sequences, and generate output signal sequences corresponding to the transmission antennas.
Abstract: A base station apparatus used in a mobile communication system where user terminals with various numbers of reception antennas may be situated includes a providing unit configured to provide plural reference signals according to the number of transmission antennas; a precoding unit configured to replicate each of a predetermined number of input signal sequences according to the number of transmission antennas, apply a predetermined precoding vector to each of the replicated sequences, and generate output signal sequences corresponding to the number of transmission antennas; and a transmitting unit configured to transmit transmission signals including the output signal sequences from plural transmission antennas; wherein at least one of the input signal sequences includes a control signal and one of the plural reference signals.
80 citations
Authors
Showing all 4032 results
Name | H-index | Papers | Citations |
---|---|---|---|
Amit P. Sheth | 101 | 753 | 42655 |
Harald Haas | 85 | 750 | 34927 |
Giuseppe Caire | 82 | 825 | 40344 |
Craig Gentry | 75 | 222 | 39327 |
Raj Jain | 64 | 424 | 30018 |
Karl Aberer | 63 | 554 | 17392 |
Fumiyuki Adachi | 54 | 1010 | 15344 |
Ismail Guvenc | 52 | 451 | 13893 |
Frank Piessens | 52 | 391 | 10381 |
Wolfgang Kellerer | 49 | 502 | 9383 |
Yoshihisa Kishiyama | 48 | 379 | 11831 |
Ravi Jain | 48 | 160 | 7467 |
Josef A. Nossek | 48 | 623 | 10377 |
Tadao Nagatsuma | 47 | 430 | 11117 |
Christian Bettstetter | 46 | 204 | 11051 |