A Practical Cooperative Multicell MIMO-OFDMA Network Based on Rank Coordination

An important challenge of wireless networks is to boost the cell edge performance and enable multi-stream transmissions to cell edge users. Interference mitigation techniques relying on multiple antennas and coordination among cells are nowadays heavily studied in the literature. Typical strategies in OFDMA networks include coordinated scheduling, beamforming and power control. In this paper, we propose a novel and practical type of coordination for OFDMA downlink networks relying on multiple antennas at the transmitter and the receiver. The transmission ranks, i.e.\ the number of transmitted streams, and the user scheduling in all cells are jointly optimized in order to maximize a network utility function accounting for fairness among users. A distributed coordinated scheduler motivated by an interference pricing mechanism and relying on a master-slave architecture is introduced. The proposed scheme is operated based on the user report of a recommended rank for the interfering cells accounting for the receiver interference suppression capability. It incurs a very low feedback and backhaul overhead and enables efficient link adaptation. It is moreover robust to channel measurement errors and applicable to both open-loop and closed-loop MIMO operations. A 20% cell edge performance gain over uncoordinated LTE-A system is shown through system level simulations.Comment: IEEE Transactions or Wireless Communications, Accepted for Publicatio

The Time-Triggered Wireless Architecture

Wirelessly interconnected sensors, actuators, and controllers promise greater flexibility, lower installation and maintenance costs, and higher robustness in harsh conditions than wired solutions. However, to facilitate the adoption of wireless communication in cyber-physical systems (CPS), the functional and non-functional properties must be similar to those known from wired architectures. We thus present Time-Triggered Wireless (TTW), a wireless architecture for multi-mode CPS that offers reliable communication with guarantees on end-to-end delays among distributed applications executing on low-cost, low-power embedded devices. We achieve this by exploiting the high reliability and deterministic behavior of a synchronous transmission based communication stack we design, and by coupling the timings of distributed task executions and message exchanges across the wireless network by solving a novel co-scheduling problem. While some of the concepts in TTW have existed for some time and TTW has already been successfully applied for feedback control and coordination of multiple mechanical systems with closed-loop stability guarantees, this paper presents the key algorithmic, scheduling, and networking mechanisms behind TTW, along with their experimental evaluation, which have not been known so far. TTW is open source and ready to use: https://ttw.ethz.ch

Control Framework for Hand-Arm Coordination

Co-ordination of multiple manipulators requires cooperation at several levels in the control hierarchy. A distributed processing environment with no hardware dependencies except at the motor servo level, would provide a flexible architecture for coordination. A system on these lines is being built to control an articulated hand and an arm. The four levels of control envisaged include a task decomposition level, a planning level, a scheduling level and a server level. The hand will carry both force and tactile sensors, feedback from these are used to provide adaptive control in grasping tasks. The processing of the sensory information is performed by independent processes, with analyzed information being sent to the relevant layer of the system. The manipulators are also controlled by individual processes. All process can open communications with an active process sending commands or data, or receiving them. We describe the scope of the system and the current setup plus future lines of development

Feedback and time are essential for the optimal control of computing systems

The performance, reliability, cost, size and energy usage of computing systems can be improved by one or more orders of magnitude by the systematic use of modern control and optimization methods. Computing systems rely on the use of feedback algorithms to schedule tasks, data and resources, but the models that are used to design these algorithms are validated using open-loop metrics. By using closed-loop metrics instead, such as the gap metric developed in the control community, it should be possible to develop improved scheduling algorithms and computing systems that have not been over-engineered. Furthermore, scheduling problems are most naturally formulated as constraint satisfaction or mathematical optimization problems, but these are seldom implemented using state of the art numerical methods, nor do they explicitly take into account the fact that the scheduling problem itself takes time to solve. This paper makes the case that recent results in real-time model predictive control, where optimization problems are solved in order to control a process that evolves in time, are likely to form the basis of scheduling algorithms of the future. We therefore outline some of the research problems and opportunities that could arise by explicitly considering feedback and time when designing optimal scheduling algorithms for computing systems

From Packet to Power Switching: Digital Direct Load Scheduling

At present, the power grid has tight control over its dispatchable generation capacity but a very coarse control on the demand. Energy consumers are shielded from making price-aware decisions, which degrades the efficiency of the market. This state of affairs tends to favor fossil fuel generation over renewable sources. Because of the technological difficulties of storing electric energy, the quest for mechanisms that would make the demand for electricity controllable on a day-to-day basis is gaining prominence. The goal of this paper is to provide one such mechanisms, which we call Digital Direct Load Scheduling (DDLS). DDLS is a direct load control mechanism in which we unbundle individual requests for energy and digitize them so that they can be automatically scheduled in a cellular architecture. Specifically, rather than storing energy or interrupting the job of appliances, we choose to hold requests for energy in queues and optimize the service time of individual appliances belonging to a broad class which we refer to as "deferrable loads". The function of each neighborhood scheduler is to optimize the time at which these appliances start to function. This process is intended to shape the aggregate load profile of the neighborhood so as to optimize an objective function which incorporates the spot price of energy, and also allows distributed energy resources to supply part of the generation dynamically.Comment: Accepted by the IEEE journal of Selected Areas in Communications (JSAC): Smart Grid Communications series, to appea