Multiuser spatial multiplexing is a downlink transmission technique that uses linear transmit pre-coding to multiplex multiple users and pre-cancel inter-user interference. In such a system the spatial degrees of freedom are used for interference mitigation and generally come at the expense of diversity gain. This paper proposes two precoding methods that use extra transmit antennas, beyond the minimum required, to provide additional degrees of diversity. The approach taken is to solve for a unitary transmit precoder, under a zero inter-user interference constraint, that minimizes an upper bound on the symbol error rate (SER) for each user. Solutions where all transmit antennas are employed as well as subsets of antennas (to reduce analog components) are described. Numerical results confirm a dramatic improvement in terms of SER and mutual information over single user MIMO methods and static allocation methods. For example, the proposed techniques achieve an SNR improvement of 6-10 dB at an uncoded SER of 10 −3, with only one extra transmit antenna.

In this paper, a novel transmission technique for the multiple-input multiple-output (MIMO) broad-cast channel is proposed that allows simultaneous transmission to multiple users with limited feedback from each user. During a training phase, the base station modulates a training sequence on multiple sets of randomly chosen orthogonal beamforming vectors. Each user sends the index of the best beamforming vector and the corresponding signal-to-interfence-plus-noise ratio for that set of orthogonal vectors back to the base station. The base station opportunistically determines the users and corresponding orthogonal vectors that maximize the sum capacity. Based on the capacity expressions, the optimal amount of training to maximize the sum capacity is derived as a function of the system parameters. The main advantage of the proposed system is that it provides throughput gains for the MIMO broadcast channel with a small feedback overhead, and provides these gains even with a small number of active users. Numerical simulations show that a 20 % gain in sum capacity is achieved (for a small number of users) over conventional opportunistic space division multiple access, and a 100 % gain (for a large number of users) over conventional opportunistic beamforming when the number of transmit antennas is four.

A major barrier for the adoption of wireless mesh networks is severe limits on throughput. Many in-network packet mixing techniques at the network layer [1], [2], [3] as well as the physical layer [4], [5], [6] have been shown to substantially improve throughput. However, the optimal mixing algorithm that maximizes throughput is still unknown. In this paper, we propose iP ack, an algorithm for in-network generation of composite packets that integrates coding at two different layers of the protocol stack: XOR-based network coding and physical layer superposition coding. Using extensive simulations, we find that the throughput gain of the joint coding iP ack algorithm is 30 % more than the better performer of network coding and superposition coding in a wide range of scenarios, and automatically takes advantage of the best available coding opportunities. In a typical wireless mesh network when more traffic is between the clients and access points, the average throughput improvement of iP ack, our joint optimization scheduler, can be 324%, while there can be little gain (less than 10%) if network coding alone is used. We also validate our results by implementing iP ack on a small-scale testbed based on GNU Radio.

A novel multiuser scheduling and feedback strategy for the multiple-input multiple-output (MIMO) downlink is proposed in this paper. It achieves multiuser diversity gain without substantial feedback requirements. The proposed strategy uses per-antenna scheduling at the base station, which maps each transmit antenna at the base station (equivalently, a spatial channel) to a user. Each user has a number of receive antennas that is greater than or equal to the number of transmit antennas at the base station. Zero-forcing receivers are deployed by each user to decode the transmitted data streams. In this system, the base station requires users ’ channel quality on each spatial channel for scheduling. An opportunistic feedback protocol is proposed to reduce the feedback requirements. The proposed protocol uses a contention channel that consists of a fixed number of feedback minislots to convey channel state information. Feedback control parameters including the channel quality threshold and the random access feedback probability are jointly adjusted to maximize the average throughput performance of this system. Multiple receive antennas at the base station are used on the feedback channel to allow decoding multiple feedback messages sent simultaneously by different users. This further reduces the bandwidth of the feedback channel. Iterative search algorithms are proposed to solve the optimization for selection of these parameters under both scenarios that the cumulative distribution functions of users are known or unknown to the base station.