In multiuser MIMO (MU-MIMO) LANs, the achievable throughput of a client depends on who is transmitting concurrently with it. Existing MU-MIMO MAC protocols, however, enable clients to use the traditional 802.11 contention to contend for concurrent transmission opportunities on the uplink. Such a contention-based protocol not only wastes lots of channel time on multiple rounds of contention but also fails to maximally deliver the gain of MU-MIMO because users randomly join concurrent transmissions without considering their channel characteristics. To address such inefficiency, this paper introduces MIMOMate, a leader-contention-based MU-MIMO MAC protocol that matches clients as concurrent transmitters according to their channel characteristics to maximally deliver the MU-MIMO gain while ensuring all users fairly share concurrent transmission opportunities. Furthermore, MIMOMate elects the leader of the matched users to contend for transmission opportunities using traditional 802.11 CSMA CA. It hence requires only a single contention overhead for concurrent streams and can be compatible with legacy 802.11 devices. A prototype implementation in USRP N200 shows that MIMOMate achieves an average throughput gain of 1.42× and $1.52× over the traditional contention-based protocol for two- and three-antenna AP scenarios, respectively, and also provides fairness for clients.
Recently, the capacity region of a multiple-input multiple-output (MIMO) Gaussian broadcast channel, with Gaussian codebooks and known-interference cancellation through dirty paper coding, was shown to equal the union of the capacity regions of a collection of MIMO multiple-access channels. We use this duality result to evaluate the system capacity achievable in a cellular wireless network with multiple antennas at the base station and multiple antennas at each terminal. Some fundamental properties of the rate region are exhibited and algorithms for determining the optimal weighted rate sum and the optimal covariance matrices for achieving a given rate vector on the boundary of the rate region are presented. These algorithms are then used in a simulation study to determine potential capacity enhancements to a cellular system through known-interference cancellation. We study both the circuit data scenario in which each user requires a constant data rate in every frame and the packet data scenario in which users can be assigned a variable rate in each frame so as to maximize the long-term average throughput. In the case of circuit data, the outage probability as a function of the number of active users served at a given rate is determined through simulations. For the packet data case, long-term average throughputs that can be achieved using the proportionally fair scheduling algorithm are determined. We generalize the zero-forcing beamforming technique to the multiple receive antennas case and use this as the baseline for the packet data throughput evaluation. It is difficult to implement optimal beamforming for multi-user multiple-input multiple-output (MIMO) downlink due to the high complexity. This paper proposes a low complexity generalized beamforming (GBF) scheme combined with an efficient user selection to maximize the weighted sum-rate. For each user, the outputs of the multiple antennas are combined with a receive GBF vector to create an equivalent multiple-input single-output (MISO) effective channel. First, user selection and receive GBF vectors are jointly optimized to construct a group of preferable effective channels. Then, transmit GBF vectors are obtained by zero-forcing over these effective channels. Simulation results show significant gain over currently known suboptimal schemes in various scenarios. 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. Abstract A study on the zero-forcing beamforming (ZFBF) scheme with antenna selection at user terminals in downlink multi-antenna multi-user systems is presented. Simulation results show that the proposed ZFBF scheme with receiver antenna selection (ZFBF-AS) achieves considerable throughput improvement over the ZFBF scheme with single receiver antenna. The results also show that, with multi-user diversity, the ZFBF-AS scheme approaches the throughput performance of the ZFBF scheme using all receiver antennas (ZFBF-WO-AS) when the base station adopts semi-orthogonal user selection (SUS) algorithm, and achieves larger throughput when the base station adopts the Round-robin scheduling algorithm. Compared with ZFBF-WO-AS, the proposed ZFBF-AS scheme can reduce the cost of user equipments and the channel state information requirement at the transmitter (CSIT) as well as the multiuser scheduling complexity at the transmitter. In multiple-antenna broadcast channels, unlike point-to-point multiple-antenna channels, the multiuser capacity depends heavily on whether the transmitter knows the channel coefficients to each user. For instance, in a Gaussian broadcast channel with M transmit antennas and n single-antenna users, the sum rate capacity scales like Mloglogn for large n if perfect channel state information (CSI) is available at the transmitter, yet only logarithmically with M if it is not. In systems with large n, obtaining full CSI from all users may not be feasible. Since lack of CSI does not lead to multiuser gains, it is therefore of interest to investigate transmission schemes that employ only partial CSI. We propose a scheme that constructs M random beams and that transmits information to the users with the highest signal-to-noise-plus-interference ratios (SINRs), which can be made available to the transmitter with very little feedback. For fixed M and n increasing, the throughput of our scheme scales as MloglognN, where N is the number of receive antennas of each user. This is precisely the same scaling obtained with perfect CSI using dirty paper coding. We furthermore show that a linear increase in throughput with M can be obtained provided that M does not not grow faster than logn. We also study the fairness of our scheduling in a heterogeneous network and show that, when M is large enough, the system becomes interference dominated and the probability of transmitting to any user converges to 1 n, irrespective of its path loss. In fact, using M= spl alpha logn transmit antennas emerges as a desirable operating point, both in terms of providing linear scaling of the throughput with M as well as in guaranteeing fairness. Achieving the capacity region in the MIMO broadcast channel requires the use of Dirty Paper Coding (DPC). When it cannot be afforded to satisfy the requirements of all users by DPC based approaches, it is necessary to identify the users which exhibit the highest performance gain compared to simpler approaches. In this paper we present a user grouping method that aims to identify those users with highest weighted sum rate gain. First some users are excluded by a simple criterion leading to a reduced user set, from which the final user group is selected by a more sophisticated criterion.