In radio, multi-user MIMO is a set of advanced MIMO, 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 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 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.
Multiple access MIMO, MIMO-SDMA, massive MIMO, cooperative MIMO, coordinated multipoint or
in other words macrodiversity, 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.
Technology MIMO
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 four to ten 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, macrodiversity MIMO, 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:
Use an existing technique with enhanced PHY capabilities, perhaps a 16×16 array configuration,
or 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. Cognitive MIMO based on intelligent techniques.
Cooperative/competitive MIMO. Cooperation: DPC, Wyner-Ziv, etc.
Competitive: Game theory, autonomous packets, implicit MAC fairness, etc.
MU-MIMO 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. Multi-user MIMO
can be generalized into two categories: MIMO broadcast channels and MIMO multiple access
channels 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, 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 enables creating parallel spatial pipes next to higher capacity
pipes through spatial multiplexing and/or diversity, by which it is able to offer superior
performance in radio multiple access communication systems. In traditional mobile cellular network
systems, the base station has no information on the position of the mobile units within
the cell and radiates the signal in all directions within the cell in order to provide radio
coverage. This results in wasting power on transmissions when there are no mobile units
to reach, in addition to causing interference for adjacent cells using the same frequency,
so called co-channel cells. Likewise, in reception, the antenna receives signals coming from all
directions including noise and interference signals. By using smart antenna technology
and by leveraging the spatial location of mobile units within the cell, space-division
multiple access techniques offer attractive performance enhancements. The radiation pattern
of the base station, both in transmission and reception, is adapted to each user to
obtain highest gain in the direction of that user. This is often done using 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.
The Base Transceiver Station can determine how distant the Mobile Station 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. 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
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. There are many potential advantages of installing
many antennas, including new SDMA and precoding techniques.
SDMA: Enabling MU-MIMO, network MIMO, 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 MIMO broadcast
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. 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. Capacity approaching schemes: DPC precoding
Near capacity: zero-forcing beamforming MIMO MAC
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. 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, Hybrid ARQ,
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 ratios can be implemented across PHYApplication 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, Amplify-and-forward, Decode-and-forward, Coded cooperation, Spatial coded cooperation,
Compress-and-forward,Non-orthogonal methods
Cooperative MIMO CO-MIMO, also known as Network MIMO, or ad
hoc MIMO, uses 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, used especially in wireless broadcasting. SFNs combined with
channel adaptive or traffic adaptive scheduling is called dynamic single frequency networks.
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 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.
Artemis demonstrated the first commercial network MIMO system in 2014, called pCell.
See also Mobile ad hoc network
Mesh network Distributed antenna system
Prisoner's dilemma Game theory
References
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, Erlangen, Germany, January 2004
E. Zimmermann, P. Herhold and G. Fettweis, On the Performance of Cooperative Relaying
Protocols in Wireless Networks., European Transactions on Telecommunications, Volume
16, Issue 1, pages 17–35. S. Shattil, Cooperative Beamforming in Wireless
Networks, U.S. Patent No. 8,670,390, filed July 22, 2005.
S. Shattil, Provisional U.S. Patent Appl. No. 60/286,850, filed April 26, 2001.