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3G MIMO

About: 3G MIMO is a(n) research topic. Over the lifetime, 9585 publication(s) have been published within this topic receiving 174383 citation(s).

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Open accessBook
David Tse1, Pramod Viswanath2Institutions (2)
01 Jan 2005-
Abstract: 1. Introduction 2. The wireless channel 3. Point-to-point communication: detection, diversity and channel uncertainty 4. Cellular systems: multiple access and interference management 5. Capacity of wireless channels 6. Multiuser capacity and opportunistic communication 7. MIMO I: spatial multiplexing and channel modeling 8. MIMO II: capacity and multiplexing architectures 9. MIMO III: diversity-multiplexing tradeoff and universal space-time codes 10. MIMO IV: multiuser communication A. Detection and estimation in additive Gaussian noise B. Information theory background.

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Topics: Multi-user MIMO (72%), Spatial multiplexing (72%), MIMO (71%) ...read more

7,400 Citations


Open accessJournal ArticleDOI: 10.1109/MCOM.2014.6736761
Abstract: Multi-user MIMO offers big advantages over conventional point-to-point MIMO: it works with cheap single-antenna terminals, a rich scattering environment is not required, and resource allocation is simplified because every active terminal utilizes all of the time-frequency bins. However, multi-user MIMO, as originally envisioned, with roughly equal numbers of service antennas and terminals and frequency-division duplex operation, is not a scalable technology. Massive MIMO (also known as large-scale antenna systems, very large MIMO, hyper MIMO, full-dimension MIMO, and ARGOS) makes a clean break with current practice through the use of a large excess of service antennas over active terminals and time-division duplex operation. Extra antennas help by focusing energy into ever smaller regions of space to bring huge improvements in throughput and radiated energy efficiency. Other benefits of massive MIMO include extensive use of inexpensive low-power components, reduced latency, simplification of the MAC layer, and robustness against intentional jamming. The anticipated throughput depends on the propagation environment providing asymptotically orthogonal channels to the terminals, but so far experiments have not disclosed any limitations in this regard. While massive MIMO renders many traditional research problems irrelevant, it uncovers entirely new problems that urgently need attention: the challenge of making many low-cost low-precision components that work effectively together, acquisition and synchronization for newly joined terminals, the exploitation of extra degrees of freedom provided by the excess of service antennas, reducing internal power consumption to achieve total energy efficiency reductions, and finding new deployment scenarios. This article presents an overview of the massive MIMO concept and contemporary research on the topic.

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  • Figure 1: Some possible antenna configurations and deployment scenarios for a massive MIMO base station.
    Figure 1: Some possible antenna configurations and deployment scenarios for a massive MIMO base station.
  • Figure 2: Relative field strength around a target terminal in a scattering environment of size 800λ×800λ, when the base station is placed 1600λ to the left. Average field strengths are calculated over 10000 random placements of 400 scatterers, when two different linear precoders are used: a) MRT precoders and b) ZF precoders. Left: pseudo-color plots of average field strengths, with target user positions at the center (?), and four other users nearby (◦). Right: average field strengths as surface plots, allowing an alternate view of the spatial focusing.
    Figure 2: Relative field strength around a target terminal in a scattering environment of size 800λ×800λ, when the base station is placed 1600λ to the left. Average field strengths are calculated over 10000 random placements of 400 scatterers, when two different linear precoders are used: a) MRT precoders and b) ZF precoders. Left: pseudo-color plots of average field strengths, with target user positions at the center (?), and four other users nearby (◦). Right: average field strengths as surface plots, allowing an alternate view of the spatial focusing.
  • Figure 3: Half the power—twice the force (from [6]): Improving uplink spectral efficiency 10 times and simultaneously increasing the radiated-power efficiency 100 times with massive MIMO technology, using extremely simple signal processing—taking into account the energy and bandwidth costs of obtaining channel state information.
    Figure 3: Half the power—twice the force (from [6]): Improving uplink spectral efficiency 10 times and simultaneously increasing the radiated-power efficiency 100 times with massive MIMO technology, using extremely simple signal processing—taking into account the energy and bandwidth costs of obtaining channel state information.
  • Figure 4: Conventional MIMO beamforming, contrasted with per-antenna constant-envelope transmission in massive MIMO. Left: conventional beamforming, where the signal emitted by each antenna has a large dynamic range. Right: per-antenna constant-envelope transmission, where each antenna sends out a signal with constant envelope.
    Figure 4: Conventional MIMO beamforming, contrasted with per-antenna constant-envelope transmission in massive MIMO. Left: conventional beamforming, where the signal emitted by each antenna has a large dynamic range. Right: per-antenna constant-envelope transmission, where each antenna sends out a signal with constant envelope.
  • Figure 5: Massive MIMO antenna arrays used for the measurements.
    Figure 5: Massive MIMO antenna arrays used for the measurements.
  • + 2

Topics: 3G MIMO (72%), Multi-user MIMO (66%), Spatial multiplexing (63%) ...read more

5,302 Citations


Journal ArticleDOI: 10.1109/MCOM.2004.1341264
Abstract: Transmit diversity generally requires more than one antenna at the transmitter. However, many wireless devices are limited by size or hardware complexity to one antenna. Recently, a new class of methods called cooperative communication has been proposed that enables single-antenna mobiles in a multi-user environment to share their antennas and generate a virtual multiple-antenna transmitter that allows them to achieve transmit diversity. This article presents an overview of the developments in this burgeoning field.

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Topics: Antenna diversity (64%), Cooperative diversity (64%), Transmit diversity (60%) ...read more

3,063 Citations


Open accessJournal ArticleDOI: 10.1109/JSAC.2003.809458
David Gesbert1, Mansoor Shafi2, Da-Shan Shiu3, Peter J. Smith4  +1 moreInstitutions (4)
Abstract: This paper presents an overview of progress in the area of multiple input multiple output (MIMO) space-time coded wireless systems. After some background on the research leading to the discovery of the enormous potential of MIMO wireless links, we highlight the different classes of techniques and algorithms proposed which attempt to realize the various benefits of MIMO including spatial multiplexing and space-time coding schemes. These algorithms are often derived and analyzed under ideal independent fading conditions. We present the state of the art in channel modeling and measurements, leading to a better understanding of actual MIMO gains. Finally, the paper addresses current questions regarding the integration of MIMO links in practical wireless systems and standards.

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  • Fig. 1. Diagram of a MIMO wireless transmission system. The transmitter and receiver are equipped with multiple antenna elements. Coding, modulation, an mapping of the signals onto the antennas may be realized jointly or separately.
    Fig. 1. Diagram of a MIMO wireless transmission system. The transmitter and receiver are equipped with multiple antenna elements. Coding, modulation, an mapping of the signals onto the antennas may be realized jointly or separately.
  • Fig. 2. Basic spatial multiplexing (SM) scheme with three TX and three RX antennas yielding three-fold improvement in spectral efficiency. Ai, Bi, and Ci represent symbol constellations for the three inputs at the various stages of transmission and reception.
    Fig. 2. Basic spatial multiplexing (SM) scheme with three TX and three RX antennas yielding three-fold improvement in spectral efficiency. Ai, Bi, and Ci represent symbol constellations for the three inputs at the various stages of transmission and reception.
  • Fig. 3. Shows the percentage relative gains in capacity due to feedback at various SNR values, channel models (K is the Ricean factor), and array sizes.
    Fig. 3. Shows the percentage relative gains in capacity due to feedback at various SNR values, channel models (K is the Ricean factor), and array sizes.
  • Fig. 4. Space–time coding.
    Fig. 4. Space–time coding.
  • Fig. 6. Performance of 4-PSK STTCs with two TX and one RX antennas.
    Fig. 6. Performance of 4-PSK STTCs with two TX and one RX antennas.
  • + 4

Topics: 3G MIMO (73%), Multi-user MIMO (70%), Spatial multiplexing (69%) ...read more

2,424 Citations


Open accessJournal ArticleDOI: 10.1109/TWC.2013.031813.120224
Rui Zhang1, Chin Keong Ho2Institutions (2)
Abstract: Wireless power transfer (WPT) is a promising new solution to provide convenient and perpetual energy supplies to wireless networks. In practice, WPT is implementable by various technologies such as inductive coupling, magnetic resonate coupling, and electromagnetic (EM) radiation, for short-/mid-/long-range applications, respectively. In this paper, we consider the EM or radio signal enabled WPT in particular. Since radio signals can carry energy as well as information at the same time, a unified study on simultaneous wireless information and power transfer (SWIPT) is pursued. Specifically, this paper studies a multiple-input multiple-output (MIMO) wireless broadcast system consisting of three nodes, where one receiver harvests energy and another receiver decodes information separately from the signals sent by a common transmitter, and all the transmitter and receivers may be equipped with multiple antennas. Two scenarios are examined, in which the information receiver and energy receiver are separated and see different MIMO channels from the transmitter, or co-located and see the identical MIMO channel from the transmitter. For the case of separated receivers, we derive the optimal transmission strategy to achieve different tradeoffs for maximal information rate versus energy transfer, which are characterized by the boundary of a so-called rate-energy (R-E) region. For the case of co-located receivers, we show an outer bound for the achievable R-E region due to the potential limitation that practical energy harvesting receivers are not yet able to decode information directly. Under this constraint, we investigate two practical designs for the co-located receiver case, namely time switching and power splitting, and characterize their achievable R-E regions in comparison to the outer bound.

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Topics: Multi-user MIMO (65%), Transmitter power output (61%), Transmitter (59%) ...read more

2,420 Citations


Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20194
201862
2017642
20161,044
20151,036
20141,230

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Topic's top 5 most impactful authors

Kentaro Nishimori

47 papers, 270 citations

Naoki Honma

38 papers, 173 citations

Robert W. Heath

35 papers, 2.2K citations

Fredrik Tufvesson

29 papers, 7.9K citations

Andrew R Nix

29 papers, 1K citations