Communications in the millimeter wave (mmWave) band faces significant challenges due to variable channels, intermittent connectivity, and high energy usage. Moreover, speeds for electronic processing of data is of the same order as typical rates for mmWave interfaces, making the use of complex algorithms for tracking channel variations and adjusting resources impractical. In order to mitigate some of these challenges, we propose an architecture that integrates the sub-6 GHz and mmWave technologies. Our system exploits the spatial correlations between the sub-6 GHz and mmWave interfaces for beamforming and data transfer . Based on extensive experimentation in indoor and outdoor settings, we demonstrate that analog beamforming can be used in mmWave without incurring large overhead, thanks to the spatial correlations with sub-6 GHz. In addition, we incorporate the sub-6 GHz interface as a fallback (secondary) data transfer mechanism such that: 1) the negative effects of highly intermittent mmWave connectivity are mitigated and 2) the abundant mmWave capacity is fully exploited. To achieve these goals, we consider the problem of scheduling the arrival traffic over the mmWave or sub-6 GHz in order to maximize the mmWave throughput while delay (due to mmWave outages) is guaranteed to be bounded. We prove using subadditivity analysis that the optimal scheduling policy is based on a single threshold that can be easily adopted despite high link variations. Numerical results demonstrate that our scheduler provides a bounded mmWave delay performance, while it achieves a similar throughput performance as the throughput-optimal policies (e.g., MaxWeight).

Out-of-Band Millimeter Wave Beamforming and Communications to Achieve Low Latency and High Energy Efficiency in 5G Systems

Backpressure-based routing and scheduling has been considered as a promising strategy for efficient resource allocation in wireless multihop networks. It has many attractive features such as throughput optimality, achievable adaptive resource allocation, support for agile load-aware routing, and simplicity. In this article, we first categorize existing backpressure-based protocols based on different design criteria and then summarize several key issues faced in the design of efficient backpressure-based protocols. We present a comprehensive survey of state-of-theart backpressure-based protocols for wireless multihop networks. We illustrate how each of the protocols works, and discuss their merits and deficiencies. Finally, we point out some future directions for supporting efficient backpressure- based routing and scheduling.

Backpressure-based routing and scheduling protocols for wireless multihop networks: A survey

Cache-enabled network architecture has great potential for enhancing the efficiency of content distribution as well as reducing the network congestion. This, in turn, has called for joint optimization of traffic engineering and caching strategies while considering both network congestion and content demands. In this paper, we present a distributed framework for joint request/data forwarding and dynamic cache placement in cache-enabled networks. Specifically, to retrieve the information about content demands and network congestion over the network, we establish a dual queue system for both requests and data, and define a dynamic mapping between the two queues with the help of dummy data such that the nodes can determine packet forwarding and caching strategies based only on local information. As the local objective function associated with Lyapunov optimization is time-varying due to the stochastic evolution of request/data queues, we develop a low-complexity distributed forwarding and caching algorithm via stochastic network utility maximization. We also prove the proposed algorithm achieves queue stability, and derive its region stability property for time-varying local optimization to demonstrate the convergence behavior. The simulation results verify queue stability and shows the proposed algorithm outperforms the existing ones.

Distributed Packet Forwarding and Caching Based on Stochastic Network Utility Maximization

The problem of controlling traffic lights under adaptive routing of vehicles in urban road networks is considered. Multi-commodity back-pressure algorithms, originally developed for routing and scheduling in communication networks, are applied to road networks to control traffic lights and adaptively reroute vehicles. The performance of the algorithms is analyzed using a microscopic traffic simulator. The results demonstrate that the proposed signal control and adaptive routing algorithms can provide significant improvement over a fixed schedule and a single-commodity back-pressure signal controller, in terms of various performance metrics, including queue-length, trips completed, and travel times.

https://publications.lib.chalmers.se/records/fulltext/216049/local_216049.pdf

Traffic-adaptive signal control and vehicle routing using a decentralized back-pressure method

In this paper, we design a new virtual queue-based back-pressure scheduling algorithm (VBR) for achieving significant delay reduction in wireless sensor networks (WSN). Our algorithm design comes from an observation that classical back-pressure scheduling algorithm usually needs a long period of time to form a queue backlog-based gradient in a network, which decreases towards the sink in the network, before achieving stable packet delivery performance. To address this issue, VBR is designed to pre-build proper virtual queue-based gradient at nodes in a WSN, which is chosen to be a function of traffic arrival rate, link rate, and distance to sink, in order to be adaptive to different network and application environments while achieving high network performance. Moreover, the queue backlog differential between each pair of neighbor nodes is decided by their actual queue lengths and also their virtual queue lengths (gradient values). We prove that VBR can maintain back-pressure scheduling’s throughput optimality. Simulation result shows that VBR can obtain significant performance improvement in terms of packet delivery ratio, average end-to-end delay, and average queue length as compared with existing work.

A virtual queue-based back-pressure scheduling algorithm for wireless sensor

Back-pressure-based adaptive routing algorithms where each packet is routed along a possibly different path have been extensively studied in the literature. However, such algorithms typically result in poor delay performance and involve h igh complexity implementation. In this paper, we develop a new adaptive routing algorithm built upon the widely studied back- pressure algorithm. We decouple the routing and scheduling components of the algorithm by designing a probabilistic routing table that is used to route packets to per-destination queues. The scheduling decisions in the case of wireless networks are made using counters called shadow queues. The results are also extended to the case of networks that employ simple forms of network coding. In that case, our algorithm provides a low-complexity solution to optimally exploit the routing–coding tradeoff.

Back-Pressure-Based Packet-by-Packet Adaptive Routing in Communication Networks

This paper shows a method to introduce a mobility aid for blind persons by giving alert to blind person using voice processor with ear phones This system is also used in automatic robots, self propelling vehicles in automated production factories etc This system contains a signal processing unit with LPC 2148 microcontroller This receives data from serial input/output port and gives alert to blind people This paper contains temperature compensation method to reduce the error in measurement of distance using ultrasonic sensors Signal processing is done using lpc2148 micro controller which is used for interfacing between different sensors and pc sensor then process it and delivers it to the computer using serial input/output port  and gives alert to blind people This paper contains temperature compensation method to reduce the error in measurement of distance using ultrasonic sensors Signal processing is done using LPC 2148 micro controller which is used for interfacing between different sensors and pc Further received data is verified using MATLAB

L. Praveen Kumar

Papers

Back-Pressure-Based Packet-by-Packet Adaptive Routing in Communication Networks

Implementation of ultrasonic ranging and fire safety for blind person