An Overview of MAS Principles

A complete and technically thorough exposition of the principles of multi-antenna signal processing (MAS) is a book-length subject. Our more modest goal here is to provide you a brief introduction to some of the many dimensions of consideration in MAS architectures and to describe a number of approaches that are frequently heard in the industry's current discourse in this area. Our next section on MAS in Practice offers our assessment of the absolute or relative performance gains of these various approaches and their domains of best application.

The Basic Architecture Choices

All MAS architectures start with the same basic principles: they involve two or more antennas on one or both ends of the communication link (i.e. the base station and/or the client device), and they perform some degree of coordinated processing on the signals to and/or from these antennas. From there, the key design choices to be made and variables to take into account include:

• The number of receive and transmit radio chains in the base station
• The number of receive and transmit radio chains on the subscriber device
• Benefits sought (which of the list in the next section below are being pursued?)
• The categories of MAS algorithms employed on the traffic channels, and on which directions and ends of the link (uplink and/or downlink, transmit and/or receive)
• Approach to control channel processing
• Degree and character of coordination between physical-layer processing (where MAS is done) and the media-access layer (scheduling)
• Approach to transmit calibration

Systems engineering of MAS-enabled networks involves making the optimum set of these basic architecture choices in the context of:

• Air interface accommodation of or compatibility with MAS (not all are equally well-suited to MAS implementation)
• Functional flexibility — are all users in the cell restricted to the same processing modes, algorithms, and antenna count, or can the system optimize for heterogeneous conditions with multiple approaches?
• The many attributes of the application itself: i.e. the network operation scenario(s) to be supported — network scale, loading, spectrum allocation, service definition, subscriber behavior (including mobility), cost and complexity constraints, especially on siting and client devices, greenfield vs. upgrade deployment, and so on.

Gains and Benefits

All MAS architectures and processing approaches leverage some combination of the following four gains and benefits:

Spatial Diversity . . . takes advantage of inherent channel differences, where they exist, between antennas separated in space. Spatial diversity is only useful when not all of the channels are in deep fades at the same time, the likelihood of which is positively correlated to the amount of scattering in the environment.

Coherent (or Combining) Gain . . . uses an understanding of the characteristics of the radio channel (channel state information) to weight the signals to or from multiple antennas to create maximum coherently-combined signal (or sensitivity) in the radio-space direction of interest. This additionally provides some amount of passive interference mitigation, as the more-focused energy distribution reduces inherent co-channel interference to some degree. Approaches tapping coherent gains are often referred to as "beamforming".

Interference Mitigation . . . adds calculations to the coherent combining gain baseline in order to send or receive the absence of energy in the radio-space direction of co-channel interferers. This is often referred to as "nulling" or active interference cancellation.

Spatial Multiplexing . . . is an application of coherent processing to resolve two or more distinct information streams from the same radio resource (or channel) at the same time in two different places in radio and physical space. These information streams can be combined at a single receiving endpoint (base station or client device) to enhance the data rate for a single link — the WiMAX Matrix B flavor of MIMO is an example of this — or they can be resolved at different endpoints (e.g. different client devices) to enhance system capacity through higher spectrum re-use — this is also called spatial division multiple access, or SDMA.

These benefits (illustrated below) are additive — it is entirely possible (as is the case for ArrayComm's A‑MAS™ software solutions for WiMAX, HC-SDMA, and PHS) to leverage all four in the same system.

All MAS solutions employ some combination of these basic forms of gains or benefits.

Current Approaches

The wireless research community and a growing number of equipment manufacturers are actively exploring a wide variety of MAS algorithms and architectures. Each varies in the extent to which it takes advantage of the full set of possible gains, the number of antennas it requires to operate with reasonable real-world performance, and in its approach to capturing channel state information. Before offering a comparative assessment of the most common approaches, it is helpful to define them in general terms:

Switched Diversity — The simplest (and least effective) approach to capturing diversity gains, this involves selecting the single antenna with the best channel at a given time. There is no attempt to combine signals from the multiple antennas available.

Beam Switching — This is effectively microsectorization, involving a fixed pattern of some number of beams per sector on the base station side, created through array processing rather than physical directional antennas. For a given subscriber, the base station chooses which beam will provide the best signal. Beam switching captures diversity and combining gains, but to an extent correlated with the degree to which the subscriber of interest is located on the centerline of a beam.

Beam Steering — Experiments with this approach have focused on base station implementations. Here a single beam per sector is created and "pointed" through array processing to correspond to the degree of arrival (DoA) of signal from the user of interest. Beam steering captures diversity and combining benefits, to the extent the DoA information accurately represents useful channel state information.

MRC — Maximum ratio combining is a simple processing technique that uses pilot or control channel signals to estimate channel characteristics for multiple antennas and then apply weights to each antenna to maximize signal to noise ratio for the summed signal (hence the name). MRC captures diversity and combining gains but does not involve active interference mitigation or spatial multiplexing in any way. MMSE, or minimum mean squared error, is another variation on this receive-processing approach.

AAS — Adaptive antenna systems take the basic concept of MRC a few steps further — by building a richer model of the channel using training data embedded in the traffic channel that enables focusing more closely on users of interest and de-focusing on interferers in both transmit and receive. AAS captures diversity, combining, and interference rejection gains.

SDMA — Spatial division multiple access utilizes AAS to enable spatial multiplexing of any given sub-channel to/from more than one client device at the same time.

Matrix A — In the WiMAX environment, space-time coding (STC, also known as Alamouti coding) is known as Matrix A MIMO. This technology captures diversity gains by sending a single data stream in two parts out of two antennas, interleaved with transformed versions of the same information, so that the receiver has higher probability of extracting the desired signal successfully. Matrix A achieves a spatial diversity order of two, but does not leverage combining, interference mitigation, or spatial multiplexing effects.

Enhanced Matrix A — The "vanilla" STC approach performs poorly in multi-cell networks with any loading at all, since the algorithm provides diversity to both signal and interference for co-channel users equally. ArrayComm has developed an approach to STC receive processing on two-antenna clients that addresses this issue. Enhanced Matrix A provides benefits in the same category as "vanilla" Matrix A, i.e. diversity gains, but more consistently across loading scenarios.

Matrix B — In WiMAX, spatial multiplexing on downlink is called Matrix B MIMO. This is roughly equivalent to SDMA in function, except that the spatial channels are used to communicate data to two or more different antennas on a single client device.

Enhanced Matrix B — The "vanilla" Matrix B processing defined in the WiMAX profile spec does not include explicit interference mitigation, and as such the performance of Matrix B degrades significantly in loaded networks — to the point where it can only be used by client devices very close to base stations. ArrayComm is developing an approach to Matrix B that addresses this issue.

MIMO — as the definitions of Matrix A and Matrix B suggest, the term MIMO is an ambiguous label for a MAS architecture. Narrowly, the acronym itself means simply "multiple inputs, multiple outputs" (referring to the channel). MIMO physical architectures can support diversity techniques such as STC, AAS functionality, as well as spatial multiplexing or SDMA.

Collaborative Spatial Multiplexing — CSM is a flavor of uplink SDMA and is typically limited to low-interference scenarios.

Ranging Extension — The baseline WiMAX profile includes a ranging channel architecture that can, under many conditions, suffer from a significant coverage shortfall relative to the traffic channel. ArrayComm has developed a profile-compliant multi-antenna signal processing approach for the ranging channel that addresses this issue.

See our next section on MAS in Practice for a comparative assessment of these various approaches.