World Library  
Flag as Inappropriate
Email this Article

Multi-user MIMO

Article Id: WHEBN0011822678
Reproduction Date:

Title: Multi-user MIMO  
Author: World Heritage Encyclopedia
Language: English
Subject: Channel state information, Macrodiversity, Multi-objective optimization
Publisher: World Heritage Encyclopedia

Multi-user MIMO

In radio, multi-user MIMO (MU-MIMO) is a set of advanced MIMO (pronounced mee-moh or my-moh), multiple-input and multiple-output, technologies where the available antennas are spread over a multitude of independent access points and independent radio terminals - each having one or multiple antennas. In contrast, single-user MIMO considers a single multi-antenna transmitter communicating with a single multi-antenna receiver. To enhance the communication capabilities of all terminals, MU-MIMO applies an extended version of space-division multiple access (SDMA) to allow multiple transmitters to send separate signals and multiple receivers to receive separate signals simultaneously in the same band. PU2RC is a fundamental and practical MU-MIMO technology for broadcast and multiple access wireless communications.

Like the relationship between OFDM and OFDMA, MU-MIMO (and, similarly, SDMA) can be thought of as an extension of MIMO applied in various ways as a multiple access strategy. A significant difference is that the performance of MU-MIMO relies on precoding capability than OFDMA so that if the transmitter does not use precoding, the performance advantage of MU-MIMO is not achievable.[1]

Multiple access MIMO, MIMO-SDMA,[2][1] massive MIMO,[3] cooperative MIMO, coordinated multipoint (CoMP) or in other words macrodiversity,[4] and ad hoc MIMO are all family terminologies within MU-MIMO, as each of those technologies leverages multiple users as a degree of freedom in achieving successful radio transmission.



To achieve MIMO from a conventional SISO system, several technologies have been proposed.

  • Beamforming alters the phase of each element in an antenna array to create spatial beam patterns through constructive and destructive interference.
  • Space-time coding/processing performs antenna diversity with multiple antennas at either transmitter or receiver side or both sides, where every antenna element is separated from its nearest element by around 4 to 10 times the wavelength to keep the signal through each multi-path independent. The distance between two adjacent antenna elements is relying on the angular spread of the beam signal.
  • SDMA is a common and typical multiple input multiple output scheme in cellular wireless systems. SDMA is often referred to as simply a MIMO system since the half port of a SDMA system also consists of multiple users. Although SDMA is indeed a MIMO technique, MIMO is not necessarily SDMA.
  • Spatial multiplexing is performed by multiple antennas equipped at both a transmitter and a receiver front end.
  • Cooperation are known as network MIMO systems, distributed MIMO systems or virtual antenna array systems. Mobile devices use the partnered mobile devices' antennas, antenna arrays, or antenna elements as virtual antennas.
  • Combinations of above techniques, etc.

MIMO enhancement

Enhancement techniques can be categorized into evolutionary and revolutionary approaches:

  • Evolutionary approaches:
    1. Use an existing technique with enhanced PHY capabilities, perhaps a 16×16 array configuration, or
    2. Use new MIMO algorithms such as precoding or multi-user scheduling at the transmitter.
  • Revolutionary approaches: developing fundamentally new MIMO concepts. Examples of revolution approaches are cooperative and virtual antenna MIMO and intelligent spatial processing such as RADAR beamforming.

Here, based on the literature, we summarize a number of advanced MIMO techniques that leverage multiple users:

  • Cross-layer MIMO: Scheduling, etc.
  • Advanced decoding MIMO: Multi-user detection such as MLD.
  • Beamforming and SDMA: widely known multi-user MIMO scheme.
  • Infrared/Non-infrared network optimization.
  • Network MIMO (Net-MIMO).
  • Cognitive MIMO based on intelligent techniques.
  • Cooperative/competitive MIMO.
  • Cooperation: DPC, Wyner-Ziv, etc.
  • Competitive: Game theory, autonomous packets, implicit MAC fairness, etc.


Multi-user MIMO can leverage multiple users as spatially distributed transmission resources, at the cost of somewhat more expensive signal processing. In comparison, conventional, or single-user MIMO considers only local device multiple antenna dimensions. Multi-user MIMO algorithms are developed to enhance MIMO systems when the number of users, or connections, numbers greater than one (admittedly, a useful concept). Multi-user MIMO can be generalized into two categories: MIMO broadcast channels (MIMO BC) and MIMO multiple access channels (MIMO MAC) for downlink and uplink situations, respectively. Single-user MIMO can be represented as point-to-point, pairwise MIMO.

To remove ambiguity of the words receiver and transmitter, we can adopt the terms access point (AP; or, base station), and user. An AP is the transmitter and a user is the receiver for downlink environments, whereas an AP is the receiver and a user is the transmitter for uplink environments. Homogeneous networks are somewhat freed from this distinction.

Space-division multiple access

Space-Division Multiple Access (SDMA) enables creating phased array techniques.

In GSM cellular networks, the base station is aware of the mobile phone's position by use of a technique called Timing Advance (TA). The Base Transceiver Station (BTS) can determine how distant the Mobile Station (MS) is by interpreting the reported TA. This information, along with other parameters, can then be used to power down the BTS or MS, if a power control feature is implemented in the network. The power control in either BTS or MS is implemented in most modern networks, especially on the MS, as this ensures a better battery life for the MS and thus a better user experience (in that the need to charge the battery becomes less frequent). This is why it may actually be safer to have a BTS close to you as your MS will be powered down as much as possible. For example, there is more power being transmitted from the MS than what you would receive from the BTS even if you are 6 m away from a mast. However, this estimation might not consider all the MS's that a particular BTS is supporting with EM radiation at any given time.

Many antennas

Main article: Many antennas

Many Antennas is a smart antenna technique, which overcomes the performance limitation of single user MIMO techniques. In cellular communications, the number of the maximum considered antennas for downlink is 2 and 4 to support LTE and IMT-A requirements, respectively. Since the available spectrum band will probably be limited while the requirement of data rate will continuously increase in beyond IMT-A to support the mobile multimedia services, it is highly probable that the number of transmit antennas at the base station must be increased up to 8-64 or more. The terminology of Massive MIMO refers to systems with hundreds of antennas at the same transmitter or receiver.[5][3] There are many potential advantages of installing many antennas, including new SDMA and precoding techniques.

SDMA: Enabling MU-MIMO, network MIMO (CoMP), and remote radio equipments

Precoding: linear precoding such as MRT, ZF and MMSE perform almost as well as non-linear precoding

There are several types of antenna array technologies. Direct antenna array: linear and 3d phased array, new structure array, and dynamic antenna array Remote and wireless antenna array: distributed antenna array and cooperative beamforming

The first and last Hop: to and from one multi-antenna user and multiple partnered users

MIMO broadcast (MIMO BC)

MIMO broadcast represents a MIMO downlink case in a single sender to multiple receiver wireless network. Examples of advanced transmit processing for MIMO BC are interference aware precoding and SDMA-based downlink user scheduling. For advanced transmit processing, the channel state information has to be known at the transmitter (CSIT). That is, knowledge of CSIT allows throughput improvement, and methods to obtain CSIT become of significant importance. MIMO BC systems have an outstanding advantage over point-to-point MIMO systems, especially when the number of transmit antennas at the transmitter, or AP, is larger than the number of receiver antennas at each receiver (user).

  • Capacity approaching schemes: DPC precoding
  • Near capacity: zero-forcing beamforming


Conversely, MIMO MAC represents a MIMO uplink case in the multiple sender to single receiver wireless network. Examples of advanced receive processing for MIMO MAC are joint interference cancellation and SDMA-based uplink user scheduling. For advanced receive processing, the receiver has to know the channel state information at the receiver (CSIR). Knowing CSIR is generally easier than knowing CSIT. However, to know CSIT costs a lot of uplink resources to transmit dedicated pilots from each user to the AP. MIMO MAC systems outperforms point-to-point MIMO systems especially when the number of receiver antennas at an AP is larger than the number of transmit antennas at each user.

Cross-layer MIMO

Cross-layer MIMO enhances the performance of MIMO links by solving certain cross-layer problems that may occur when MIMO configurations are employed in a system. Cross-layer techniques can be used to enhance the performance of SISO links as well. Examples of cross-layer techniques are Joint Source-Channel Coding, Adaptive Modulation and Coding (AMC, or "Link Adaptation"), Hybrid ARQ (HARQ), and user scheduling.

Multi-user to multi-user

The highly interconnected wireless ad hoc network increases the flexibility of wireless networking at the cost of increased multi-user interference. To improve the interference immunity, PHY/MAC-layer protocols have evolved from competition based to cooperative based transmission and reception. Cooperative wireless communications can actually exploit interference, which includes self-interference and other user interference. In cooperative wireless communications, each node might use self-interference and other user interference to improve the performance of data encoding and decoding, whereas conventional nodes are generally directed to avoid the interference. For example, once strong interference is decodable, a node decodes and cancels the strong interference before decoding the self-signal. The mitigation of low Carrier over Interference (CoI) ratios can be implemented across PHY/MAC/Application network layers in cooperative systems.

  • Cooperative multiple antenna research — Apply multiple antenna technologies in situations with antennas distributed among neighboring wireless terminals.
    • Cooperative diversity — Achieve antenna diversity gain by the cooperation of distributed antennas belonging to each independent node.
    • Cooperative MIMO — Achieve MIMO advantages, including the spatial multiplexing gain, using the transmit or receiver cooperation of distributed antennas belonging to many different nodes.
  • Cooperative relay — Apply cooperative concepts onto relay techniques, which is similar to cooperative diversity in terms of cooperative signalling. However, the main criterion of cooperative relay is to improve the tradeoff region between delay and performance, while that of cooperative diversity and MIMO is to improve the link and system performance at the expense of minimal cooperation loss.
  • Relaying techniques for cooperation
    • Store-and-forward (S&F), Amplify-and-forward (A&F), Decode-and-forward (D&F), Coded cooperation, Spatial coded cooperation, Compress-and-forward (C&F),Non-orthogonal methods

Cooperative MIMO (CO-MIMO)

CO-MIMO, also known as Network MIMO (Net-MIMO), or ad hoc MIMO, utilizes distributed antennas which belong to other users, while conventional MIMO, i.e., single-user MIMO, only employs antennas belonging to the local terminal. CO-MIMO improves the performance of a wireless network by introducing multiple antenna advantages, such as diversity, multiplexing and beamforming. If the main interest hinges on the diversity gain, it is known as cooperative diversity. It can be described as a form of macro-diversity, used for example in soft handover. Cooperative MIMO corresponds to transmitter macro-diversity or simulcasting. A simple form that does not require any advanced signal processing is single frequency networks (SFN), used especially in wireless broadcasting. SFNs combined with channel adaptive or traffic adaptive scheduling is called dynamic single frequency networks (DSFN).

CO-MIMO is a technique useful for future cellular networks which consider wireless mesh networking or wireless ad hoc networking. In wireless ad hoc networks, multiple transmit nodes communicate with multiple receive nodes. To optimize the capacity of ad hoc channels, MIMO concepts and techniques can be applied to multiple links between the transmit and receive node clusters. Contrasted to multiple antennas in a single-user MIMO transceiver, participating nodes and their antennas are located in a distributed manner. So, to achieve the capacity of this network, techniques to manage distributed radio resources are essential. Strategies such as autonomous interference cognition, node cooperation, and network coding with dirty paper coding (DPC) have been suggested as solutions to optimize wireless network capacity.

Of analogical interest here may be the comparison between the evolution of computing cores and mobile antennas. To wit, a single high performance core is the first generation of CPU core evolution, progressing to a few cores, and then to many cores in a centralized fashion as the second step—the recent environment. It is anticipated that it will be common for cooperative work to proceed from multiple cores owned by different users, made available to the individual user in return for help with others' information processing. Such catchphrases include ambient intelligence, wireless ubiquitous computing, and the semantic web.

See also


Further reading

  • C. B. Chae, D. Mazzarese, N. Jindal, and R. W. Heath, Jr., Coordinated Beamforming with Limited Feedback in the MIMO Broadcast Channel, IEEE Jour. on Selected Topics in Comm., 2008.
  • P. Herhold, E. Zimmermann and G. Fettweis, On the Performance of Cooperative Amplify-and-Forward Relay Networks., 5th International ITG Conference on Source and Channel Coding (SCC), Erlangen, Germany, January 2004
  • E. Zimmermann, P. Herhold and G. Fettweis, On the Performance of Cooperative Relaying Protocols in Wireless Networks., (Preprint version of the Journal article) European Transactions on Telecommunications (ETT), Volume 16, Issue 1 (January–February 2005), pages 17–35.
  • S. Shattil, Cooperative Beamforming in Wireless Networks, U.S. Patent Appl. 11/187107, filed July 22, 2005.
This article was sourced from Creative Commons Attribution-ShareAlike License; additional terms may apply. World Heritage Encyclopedia content is assembled from numerous content providers, Open Access Publishing, and in compliance with The Fair Access to Science and Technology Research Act (FASTR), Wikimedia Foundation, Inc., Public Library of Science, The Encyclopedia of Life, Open Book Publishers (OBP), PubMed, U.S. National Library of Medicine, National Center for Biotechnology Information, U.S. National Library of Medicine, National Institutes of Health (NIH), U.S. Department of Health & Human Services, and, which sources content from all federal, state, local, tribal, and territorial government publication portals (.gov, .mil, .edu). Funding for and content contributors is made possible from the U.S. Congress, E-Government Act of 2002.
Crowd sourced content that is contributed to World Heritage Encyclopedia is peer reviewed and edited by our editorial staff to ensure quality scholarly research articles.
By using this site, you agree to the Terms of Use and Privacy Policy. World Heritage Encyclopedia™ is a registered trademark of the World Public Library Association, a non-profit organization.

Copyright © World Library Foundation. All rights reserved. eBooks from Project Gutenberg are sponsored by the World Library Foundation,
a 501c(4) Member's Support Non-Profit Organization, and is NOT affiliated with any governmental agency or department.