Overhead of Downlink Multi-User MIMO
Downlink Multi-User MIMO (MU-MIMO) enables capacity gains via simultaneous transmission from the access point (AP) to multiple users. Unfortunately, despite such high physical layer rates, a significant amount of airtime is devoted to providing the access point (transmitter) with the required Channel State Information (CSI or CSIT). Indeed, in 802.11ac, the number of required CSI feedback messages increases linearly with the number of users simultaneously served. Similarly, after every downlink MU-MIMO transmission, the number of acknowledgements (ACKs) and ACK-request exchanges between the AP and the served users also increases linearly with the number of users. The time-resources devoted to these exchanges severely reduce MU-MIMO throughput gains. The following figure shows the IEEE 802.11ac timeline of sounding and feedback process (sub-figure(a)) and acknowledgement process (sub-figure(a)).
Scalable Channel Sounding with Concurrent Spatially Multiplexed Feedback
In this project, we present CUiC to replace the aforementioned sequential CSI feedback and ACK messaging system with a design that achieves parallel transmission. We demonstrate how to scale uplink feedback by employing only a single transmission slot to simultaneously send the control messages from all users (independently of the number of users). In order for the AP to decode multiple concurrent transmissions, it needs to train its receiver to perform per-user channel estimation, trigger automatic gain control (AGC), and estimate and correct carrier frequency offsets as well as other timing offsets due to digital and RF mismatches between users and AP. Thus, to realize concurrent single-slot feedback, we demonstrate that preamble staggering of user-to-AP packets allows the AP to obtain “clean” (interference-free), per-user measurements to enable this training. Furthermore, we demonstrate that as a desirable side effect, CUiC also increases robustness of the sounding process by reducing the time between CSIT estimation and downlink data transmission, which is critical in fast fading channels or in the presence of highly mobile users. The following figures show the CUiC staggered feedback format and the geometric representation of receiver-side beamforming.
User Selection and Retransmissions
In the context of CUiC, we propose a set of policies for combining sounding and user selection, each with a different objective: (i) Basic operation (802.11ac-like): The AP collects CSIT from as many users as it has transmit antennas (maximum DoF). Regardless of the user selection algorithm employed prior to sounding, the AP collects M beamforming reports and then serves the subset of those M users that maximize the aggregate rate (two-round user selection). (ii) Maximize user diversity (mDiv): Increased user diversity leads to increased rate performance of downlink MU-MIMO. With more information about the channels to different users, the AP can select combinations of them that satisfy a certain rate or fairness criteria. CUiC increases the number of CSIT reports provided at each feedback slot by M fold, thus giving the AP M times more information compared to the single-user per feedback-slot case. If we assume that the AP can spend the same amount of time performing sounding as 802.11ac, then it can potentially acquire CSIT from M^2 users (vs. M in 802.11ac). In case there are fewer than M^2 associated users, this scheme could lead to maximum achievable rate. (iii) Minimize sounding air-time utilization (mSo): In this policy, only one feedback slot is allowed regardless of the number of successfully decoded (concurrent) streams. Similarly to the basic operation, the AP can implement a two round user selection. Notice that retransmissions are allowed in the first two policies in case the AP fails to decode at least one stream. A retransmission would allow other users to “piggyback” and join the uplink transmission on the next feedback slot (thus increasing user diversity).
O. Bejarano, S. Quadri, O. Gurewitz, and E. Knightly, “Scaling Multi-User MIMO WLANs: the Case for Concurrent Uplink Control Messages,” in Proceedings of IEEE SECON 2015, Seattle, WA, June 2015. Best Paper Award.