Joint Scheduling and ARQ for MU-MIMO Downlink in the Presence of Inter-Cell Interference

User scheduling and multiuser multi-antenna (MU-MIMO) transmission are at the core of high rate data-oriented downlink schemes of the next-generation of cellular systems (e.g., LTE-Advanced). Scheduling selects groups of users according to their channels vector directions and SINR levels. However, when scheduling is applied independently in each cell, the inter-cell interference (ICI) power at each user receiver is not known in advance since it changes at each new scheduling slot depending on the scheduling decisions of all interfering base stations. In order to cope with this uncertainty, we consider the joint operation of scheduling, MU-MIMO beamforming and Automatic Repeat reQuest (ARQ). We develop a game-theoretic framework for this problem and build on stochastic optimization techniques in order to find optimal scheduling and ARQ schemes. Particularizing our framework to the case of "outage service rates", we obtain a scheme based on adaptive variable-rate coding at the physical layer, combined with ARQ at the Logical Link Control (ARQ-LLC). Then, we present a novel scheme based on incremental redundancy Hybrid ARQ (HARQ) that is able to achieve a throughput performance arbitrarily close to the "genie-aided service rates", with no need for a genie that provides non-causally the ICI power levels. The novel HARQ scheme is both easier to implement and superior in performance with respect to the conventional combination of adaptive variable-rate coding and ARQ-LLC.Comment: Submitted to IEEE Transactions on Communications, v2: small correction

Fundamental Limits in MIMO Broadcast Channels

This paper studies the fundamental limits of MIMO broadcast channels from a high level, determining the sum-rate capacity of the system as a function of system paramaters, such as the number of transmit antennas, the number of users, the number of receive antennas, and the total transmit power. The crucial role of channel state information at the transmitter is emphasized, as well as the emergence of opportunistic transmission schemes. The effects of channel estimation errors, training, and spatial correlation are studied, as well as issues related to fairness, delay and differentiated rate scheduling

Downlink Video Streaming for Users Non-Equidistant from Base Station

We consider multiuser video transmission for users that are non-equidistantly positioned from base station. We propose a greedy algorithm for video streaming in a wireless system with capacity achieving channel coding, that implements the cross-layer principle by partially separating the physical and the application layer. In such a system the parameters at the physical layer are dependent on the packet length and the conditions in the wireless channel and the parameters at the application layer are dependent on the reduction of the expected distortion assuming no packet errors in the system. We also address the fairness in the multiuser video system with non-equidistantly positioned users. Our fairness algorithm is based on modified opportunistic round robin scheduling. We evaluate the performance of the proposed algorithms by simulating the transmission of H.264/AVC video signals in a TDMA wireless system

Sum Rates, Rate Allocation, and User Scheduling for Multi-User MIMO Vector Perturbation Precoding

This paper considers the multiuser multiple-input multiple-output (MIMO) broadcast channel. We consider the case where the multiple transmit antennas are used to deliver independent data streams to multiple users via vector perturbation. We derive expressions for the sum rate in terms of the average energy of the precoded vector, and use this to derive a high signal-to-noise ratio (SNR) closed-form upper bound, which we show to be tight via simulation. We also propose a modification to vector perturbation where different rates can be allocated to different users. We conclude that for vector perturbation precoding most of the sum rate gains can be achieved by reducing the rate allocation problem to the user selection problem. We then propose a low-complexity user selection algorithm that attempts to maximize the high-SNR sum rate upper bound. Simulations show that the algorithm outperforms other user selection algorithms of similar complexity.Comment: 27 pages with 6 figures and 2 tables. Accepted for publication in IEEE Trans. Wireless Comm

Delay aware optimal resource allocation in MU MIMO-OFDM using enhanced spider monkey optimization

In multiple users MIMO- OFDM system allocates the available resources to the optimal users is a difficult task. Hence the scheduling and resource allocation become the major problem in the wireless network mainly in case of multiple input and multiple output method that has to be made efficient. There is various method introduced to give an optimal solution to the problem yet it has many drawbacks. So we propose this paper to provide an efficient solution for resource allocation in terms of delay and also added some more features such as high throughout, energy efficient and fairness. To make optimal resource allocation we introduce optimization algorithm named spider monkey with an enhancement which provides the efficient solution. In this optimization process includes the scheduling and resource allocation, the SNR values, channel state information (CSI) from the base station. To make more efficient finally we perform enhanced spider - monkey algorithm hence the resource allocation is performed based on QoS requirements. Thus the simulation results in our paper show high efficiency when compared with other schedulers and techniques