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Spatial multiplexing

About: Spatial multiplexing is a(n) research topic. Over the lifetime, 7543 publication(s) have been published within this topic receiving 190867 citation(s).

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Papers
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Journal ArticleDOI: 10.1109/49.730453
Siavash Alamouti1Institutions (1)
Abstract: This paper presents a simple two-branch transmit diversity scheme. Using two transmit antennas and one receive antenna the scheme provides the same diversity order as maximal-ratio receiver combining (MRRC) with one transmit antenna, and two receive antennas. It is also shown that the scheme may easily be generalized to two transmit antennas and M receive antennas to provide a diversity order of 2M. The new scheme does not require any bandwidth expansion or any feedback from the receiver to the transmitter and its computation complexity is similar to MRRC.

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Topics: Transmit diversity (68%), Antenna diversity (65%), Cyclic delay diversity (60%) ...read more

13,447 Citations


Journal ArticleDOI: 10.1023/A:1008889222784
G. J. Foschini1, M. J. Gans1Institutions (1)
Abstract: This paper is motivated by the need for fundamental understanding of ultimate limits of bandwidth efficient delivery of higher bit-rates in digital wireless communications and to also begin to look into how these limits might be approached. We examine exploitation of multi-element array (MEA) technology, that is processing the spatial dimension (not just the time dimension) to improve wireless capacities in certain applications. Specifically, we present some basic information theory results that promise great advantages of using MEAs in wireless LANs and building to building wireless communication links. We explore the important case when the channel characteristic is not available at the transmitter but the receiver knows (tracks) the characteristic which is subject to Rayleigh fading. Fixing the overall transmitted power, we express the capacity offered by MEA technology and we see how the capacity scales with increasing SNR for a large but practical number, n, of antenna elements at both transmitter and receiver. We investigate the case of independent Rayleigh faded paths between antenna elements and find that with high probability extraordinary capacity is available. Compared to the baseline n = 1 case, which by Shannon‘s classical formula scales as one more bit/cycle for every 3 dB of signal-to-noise ratio (SNR) increase, remarkably with MEAs, the scaling is almost like n more bits/cycle for each 3 dB increase in SNR. To illustrate how great this capacity is, even for small n, take the cases n = 2, 4 and 16 at an average received SNR of 21 dB. For over 99% of the channels the capacity is about 7, 19 and 88 bits/cycle respectively, while if n = 1 there is only about 1.2 bit/cycle at the 99% level. For say a symbol rate equal to the channel bandwith, since it is the bits/symbol/dimension that is relevant for signal constellations, these higher capacities are not unreasonable. The 19 bits/cycle for n = 4 amounts to 4.75 bits/symbol/dimension while 88 bits/cycle for n = 16 amounts to 5.5 bits/symbol/dimension. Standard approaches such as selection and optimum combining are seen to be deficient when compared to what will ultimately be possible. New codecs need to be invented to realize a hefty portion of the great capacity promised.

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Topics: Symbol rate (57%), Fading (54%), Communication channel (54%) ...read more

10,358 Citations


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


Journal ArticleDOI: 10.1002/BLTJ.2015
Gerard J. Foschini1Institutions (1)
Abstract: This paper addresses digital communication in a Rayleigh fading environment when the channel characteristic is unknown at the transmitter but is known (tracked) at the receiver. Inventing a codec architecture that can realize a significant portion of the great capacity promised by information theory is essential to a standout long-term position in highly competitive arenas like fixed and indoor wireless. Use (n T , n R ) to express the number of antenna elements at the transmitter and receiver. An (n, n) analysis shows that despite the n received waves interfering randomly, capacity grows linearly with n and is enormous. With n = 8 at 1% outage and 21-dB average SNR at each receiving element, 42 b/s/Hz is achieved. The capacity is more than 40 times that of a (1, 1) system at the same total radiated transmitter power and bandwidth. Moreover, in some applications, n could be much larger than 8. In striving for significant fractions of such huge capacities, the question arises: Can one construct an (n, n) system whose capacity scales linearly with n, using as building blocks n separately coded one-dimensional (1-D) subsystems of equal capacity? With the aim of leveraging the already highly developed 1-D codec technology, this paper reports just such an invention. In this new architecture, signals are layered in space and time as suggested by a tight capacity bound.

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Topics: Fading (55%), Bell Laboratories Layered Space-Time (54%), Transmitter (53%) ...read more

6,728 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 7: Achieved downlink sum-rates, using MRT precoding, with four single-antenna terminals and between 4 and 128 base station antennas.
    Figure 7: Achieved downlink sum-rates, using MRT precoding, with four single-antenna terminals and between 4 and 128 base station antennas.
  • 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 6: CDF of the singular value spread for MIMO systems with 4 terminals and three different numbers of BS antennas: 4, 32, and 128. The theoretical i.i.d. channel is shown as a reference, while the other two cases are measured channels with linear and cylindrical array structures at the BS. Note: The curve for the linear array coincides with that of the i.i.d. channel for 4 BS.
    Figure 6: CDF of the singular value spread for MIMO systems with 4 terminals and three different numbers of BS antennas: 4, 32, and 128. The theoretical i.i.d. channel is shown as a reference, while the other two cases are measured channels with linear and cylindrical array structures at the BS. Note: The curve for the linear array coincides with that of the i.i.d. channel for 4 BS.
  • Figure 5: Massive MIMO antenna arrays used for the measurements.
    Figure 5: Massive MIMO antenna arrays used for the measurements.
  • 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.
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Topics: 3G MIMO (72%), Multi-user MIMO (66%), Spatial multiplexing (63%) ...read more

5,302 Citations


Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2021133
2020170
2019217
2018225
2017408
2016513

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Topic's top 5 most impactful authors

Robert W. Heath

82 papers, 8.7K citations

Arogyaswami Paulraj

36 papers, 6.6K citations

Angela Doufexi

28 papers, 280 citations

Harald Haas

27 papers, 1.4K citations

Andrew R Nix

25 papers, 855 citations

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