We consider the proportional fair rate allocation in an 802.11 WLAN that supports multi-user MIMO (MU-MIMO) transmission by one or more stations. We characterise, for the first time, the proportional fair allocation of MU-MIMO spatial streams and station transmission opportunities. While a number of features carry over from the case without MU-MIMO, in general neither flows nor stations need to be allocated equal airtime when MU-MIMO is available.
In @cite_6 the authors propose a novel MAC design with opportunistic MU-MIMO scheduling based on channel sounding feedback, where packets are selected depending on their transmission duration and type of traffic. In @cite_2 is also proposed a novel MAC design for MU-MIMO that focusses on issues such as MAC ACKing of MU-MIMO transmissions. Packets are scheduled for transmission using a weighted queuing mechanism that considers both packets acknowledgements and type of traffic. However, in both @cite_6 @cite_2 fairness and allocation of MU-MIMO transmission patterns amongst flows is not considered. The work in @cite_8 focusses on packet aggregation in an IEEE 802.11ac AP, and considers a fixed MU-MIMO schedule where one flow is allocated per spatial stream. Regarding utility fairness in WLANs, in @cite_1 is presented the first rigorous analysis of proportional fairness in 802.11 WLANs where transmissions are to a single destination.
@cite_8 @cite_1 @cite_6 @cite_2
1978717380 2099243528 2164105463 2112490266
We consider the proportional fair rate allocation in an 802.11 WLAN that supports multi-user MIMO (MU-MIMO) transmission by one or more stations. We characterise, for the first time, the proportional fair allocation of MU-MIMO spatial streams and station transmission opportunities. While a number of features carry over from the case without MU-MIMO, in general neither flows nor stations need to be allocated equal airtime when MU-MIMO is available. Multi-user spatial multiplexing combined with packet aggregation can significantly increase the performance of Wireless Local Area Networks (WLANs). In this letter, we present and evaluate a simple technique to perform packet aggregation in IEEE 802.11ac MU-MIMO (Multi-user Multiple Input Multiple Output) WLANs. Results show that in non-saturation conditions both the number of active stations (STAs) and the queue size have a significant impact on the system performance. If the number of STAs is excessively high, the heterogeneity of destinations in the packets contained in the queue makes it difficult to take full advantage of packet aggregation. This effect can be alleviated by increasing the queue size, which increases the chances of scheduling a large number of packets at each transmission, hence improving the system throughput at the cost of a higher delay. Advances in digital communications and signal processing have enabled the adaptation of advanced communication techniques in wireless LAN (WLAN) standards. Among those advanced techniques, multiple-input-multipleoutput (MIMO) is now part of the high throughput (HT) WLAN standard, a.k.a. IEEE 802.11n. With the completion of the IEEE 802.11n specification, the IEEE 802.11 working group (WG) is now working on a new amendment to achieve very high throughput (VHT) in the gigabit range.. The move to higher data rates is enabled by introducing wider bandwidth, downlink multi-user MIMO (MU-MIMO), and higher modulation and coding schemes (MCS). This paper focuses the use of group membership and identifiers for managing downlink transmissions using MU-MIMO. Downlink MU-MIMO allows a WLAN access point to transmit to multiple stations simultaneously. Group Membership and identifiers are used to signal target stations together with their positions and the number of spatial streams intended for each of them in the downlink transmission. A description of the Group ID concept and its application to the VHT specification is discussed here. A method for assigning stations' position to Group IDs is introduced and its performance is examined. In multiuser MIMO (MU-MIMO) networks, the optimal bit rate of a user is highly dynamic and changes from one packet to the next. This breaks traditional bit rate adaptation algorithms, which rely on recent history to predict the best bit rate for the next packet. To address this problem, we introduce TurboRate, a rate adaptation scheme for MU-MIMO LANs. TurboRate shows that clients in a MU-MIMO LAN can adapt their bit rate on a per-packet basis if each client learns two variables: its SNR when it transmits alone to the access point, and the direction along which its signal is received at the AP. TurboRate also shows that each client can compute these two variables passively without exchanging control frames with the access point. A TurboRate client then annotates its packets with these variables to enable other clients to pick the optimal bit rate and transmit concurrently to the AP. A prototype implementation in USRP-N200 shows that traditional rate adaptation does not deliver the gains of MU-MIMO WLANs, and can interact negatively with MU-MIMO, leading to low throughput. In contrast, enabling MU-MIMO with TurboRate provides a mean throughput gain of 1.7x and 2.3x, for 2-antenna and 3-antenna APs respectively.