Controlling robots in real-time over a wireless interface present fundamental challenges for forthcoming fifth generation wireless networks. Mission critical real-time applications such as telesurgery over the tactile Internet require a communication link that is both ultra-reliable and low-latency, and that simultaneously serving multiple devices and applications. Wireless performance requirements for these applications surpass the capabilities of current wireless cellular standards. The prevailing ambitions for the fifth generation wireless specifications go beyond higher throughput and embrace the wireless performance demands of mission critical real-time applications in robotics and the Internet of Things. To accommodate these demands, changes have to be made across all layers of the wireless infrastructure. The fifth generation wireless standards are far from finalized but massive Multiple-Input Multiple-Output has surfaced as a strong radio access technology candidate and has great potential to cope with all these stringent requirements. In this paper, we investigate how Ultra-Reliable and Low-Latency Communication with massive MIMO can be achieved for bilateral teleoperation, an integral part of the tactile Internet. We conclude through simulation what the performance bounds are for massive MIMO and thus how to configure such a system for near deterministic latency and what the inherit trade-offs are.
In this paper, optimal resource allocation policies are characterized for wireless cognitive networks under the spectrum leasing model. We propose cooperative schemes in which secondary users share the time-slot with primary users in return for cooperation. Cooperation is feasible only if the primary system's performance is improved over the non-cooperative case. First, we investigate a scheduling problem where secondary users are interested in immediate rewards. Here, we consider both infinite and finite backlog cases. Then, we formulate another problem where the secondary users are guaranteed a portion of the primary utility, on a long-term basis, in return for cooperation. Finally, we present a power allocation problem where the goal is to maximize the expected net benefit defined as utility minus cost of energy. Our proposed scheduling policies are shown to outperform non-cooperative scheduling policies, in terms of expected utility and net benefit, for a given set of feasible constraints. Based on Lyapunov optimization techniques, we show that our schemes are arbitrarily close to the optimal performance at the price of reduced convergence rate.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.