Frame aggregation

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Frame aggregation is a feature that allows communicating on a shared link or channel, typically a TDM shared channel, with a minimum time slot that for efficiency reasons benefits from filling the time slot with data, i.e. sending two or more data frames in a single transmission. The feature is an important part of the IEEE 802.11e, 802.11n and 802.11ac wireless LAN standards that increases throughput with frame aggregation. The MoCA protocol used for communication over coaxial networks also implements frame aggregation for the same reason. In protocol standards and implementations, the frame aggregation is usually combined with segmentation and reassembly of frames so that the time slots can be filled to 100%. E.g., an aggregation MAC PDU can be filled with 3.5 frames to ensure the time slot is utilized to 100% and in the next time slot the rest of the fragmented frame is sent together with any additional complete frames.

The article uses IEEE 802.11 as a basis for explanations as it is probably the most wide spread and commonly known shared channel communication solution, but the protocol features for frame aggregation are common to many other communication protocols that utilize a shared communication channel, e.g. MAC service data unit (MSDU, e.g. an Ethernet frame) aggregation and MAC protocol data unit (MPDU, e.g. IEEE 802.11n frame) naming is also used in MoCA.

Every frame transmitted by an 802.11 device has a significant amount of overhead, including radio level headers, media access control (MAC) frame fields, inter-frame spacing, and acknowledgement of transmitted frames. At the highest data rates, this overhead can consume more bandwidth than the payload data frame.^[1] To address this issue, the 802.11n standard defines two types of frame aggregation: MAC service data unit (MSDU) aggregation and MAC protocol data unit (MPDU) aggregation. Both types group several data frames into one large frame. Because management information needs to be specified only once per frame, the ratio of payload data to the total volume of data is higher, allowing higher throughput.