RFSU-MIMO vs MU-MIMO: Differences Explained
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This article compares SU-MIMO and MU-MIMO, highlighting the key differences between them in the context of 802.11ax (Wi-Fi 6), 4G/LTE, and 5G NR (New Radio) technologies.
Introduction to MIMO
MIMO stands for Multiple Input Multiple Output. It refers to a system that uses more than one antenna element to increase system capacity, throughput, or coverage. Beamforming techniques are often used to concentrate radiated energy towards a target User Equipment (UE), reducing interference to other UEs and improving coverage.
There are two major types of MIMO based on how the Base Station (BS) transmission is utilized by mobile or fixed users: SU-MIMO and MU-MIMO. Both are primarily used in the downlink direction (from the Base Station/eNB/Access Point to the users).
Another concept is massive MIMO (mMIMO), which combines multiple radio units and antenna elements on a single active antenna unit. These can house 16, 32, 64, or even 96 antenna elements. Massive MIMO employs beamforming to direct energy in the desired user direction, minimizing interference from undesired users.
SU-MIMO (Single-User MIMO)
- In SU-MIMO, all the streams of antenna arrays are focused on a single user.
- Hence, it’s referred to as Single User MIMO.
- It splits the available Signal-to-Interference-plus-Noise Ratio (SINR) between different multiple data layers directed at the target UE simultaneously, with each layer being separately beamformed. This increases peak user throughput and system capacity.
- In this configuration, the cell communicates with a single user at a time.
- Advantages: No significant interference concerns.
The figure depicts SU-MIMO and MU-MIMO concepts in an IEEE 802.11ax (Wi-Fi 6) system. It shows a Wi-Fi 6 compliant AP (Access Point) and Wi-Fi 6 stations/users/clients.
MU-MIMO (Multi-User MIMO)
- In MU-MIMO, multiple streams are focused on multiple users. Moreover, each of these streams provides radiated energy to more than one user.
- Hence, it is referred to as Multi User MIMO.
- It shares the available SINR between multiple data layers towards multiple UEs simultaneously, with each layer being separately beamformed. This increases overall system capacity and user-perceived throughput.
- Here, the cell communicates with multiple users concurrently.
- Advantages: Multiplexing gain.
The figure depicts MU-MIMO used in a mMIMO system in 5G. As shown, multiple data streams (of multiple users) are passed through layer mapping/precoding before they are being mapped to antenna array elements and transmitted over the air.
Tabular Difference Between SU-MIMO and MU-MIMO
| Features | SU-MIMO | MU-MIMO |
|---|---|---|
| Full Form | Single User MIMO | Multi User MIMO |
| Function | It is the mechanism in which information of single user is transmitted simultaneously over more than one data stream by BS in same time/frequency resources. | In MU-MIMO, data streams are distributed across multiple users on same time/frequency resources but dependent upon spatial separation. |
| Major Objective | It helps in increasing user/link data rate as it is function of bandwidth and power availability. | It helps in increasing system capacity i.e. number of users supported by base station. |
| Performance Impact (Antenna Correlation) | More susceptible | Less susceptible |
| Performance Impact (Source of interference) | Adjacent co-channel cells | Links supporting same cell and other MU-MIMO users, and adjacent co-channel cells |
| Power allocation | Split between multiple layers to same user. Fixed per transmit antenna | Shared between multi-users and multiple layers. It can be allocated per MU-MIMO user based on channel condition. |
| CSI/Feedback process | Varies upon implementation, TDD or FDD and reciprocity or feedback based. Less susceptible on feedback granularity and quality | Very dependent upon CSI for channel estimation accuracy. More susceptible on feedback granularity and quality |
| Beamforming dependency | Varies upon implementation TDD or FDD and reciprocity or feedback based. Less susceptible on feedback granularity and quality | Greatly assisted by appropriate beamforming mechanisms (spatial focusing) which maximizes gain towards the intended users. More susceptible on feedback granularity and quality |
