125 research outputs found
Stabilizing Stochastic Predictive Control under Bernoulli Dropouts
This article presents tractable and recursively feasible optimization-based
controllers for stochastic linear systems with bounded controls. The stochastic
noise in the plant is assumed to be additive, zero mean and fourth moment
bounded, and the control values transmitted over an erasure channel. Three
different transmission protocols are proposed having different requirements on
the storage and computational facilities available at the actuator. We optimize
a suitable stochastic cost function accounting for the effects of both the
stochastic noise and the packet dropouts over affine saturated disturbance
feedback policies. The proposed controllers ensure mean square boundedness of
the states in closed-loop for all positive values of control bounds and any
non-zero probability of successful transmission over a noisy control channel
Data Transmission Over Networks for Estimation and Control
We consider the problem of controlling a linear time invariant process when the controller is located at a location remote from where the sensor measurements are being generated. The communication from the sensor to the controller is supported by a communication network with arbitrary topology composed of analog erasure channels. Using a separation principle, we prove that the optimal linear-quadratic-Gaussian (LQG) controller consists of an LQ optimal regulator along with an estimator that estimates the state of the process across the communication network. We then determine the optimal information processing strategy that should be followed by each node in the network so that the estimator is able to compute the best possible estimate in the minimum mean squared error sense. The algorithm is optimal for any packet-dropping process and at every time step, even though it is recursive and hence requires a constant amount of memory, processing and transmission at every node in the network per time step. For the case when the packet drop processes are memoryless and independent across links, we analyze the stability properties and the performance of the closed loop system. The algorithm is an attempt to escape the viewpoint of treating a network of communication links as a single end-to-end link with the probability of successful transmission determined by some measure of the reliability of the network
Optimal LQG Control Across a Packet-Dropping Link
We examine optimal Linear Quadratic Gaussian control for a system in which communication between the sensor (output of the plant) and the controller occurs across a packet-dropping link. We extend the familiar LQG separation principle to this problem that allows us to solve this problem using a standard LQR state-feedback design, along with an optimal algorithm for propagating and using the information across the unreliable link. We present one such optimal algorithm, which consists of a Kalman Filter at the sensor side of the link, and a switched linear filter at the controller side. Our design does not assume any statistical model of the packet drop events, and is thus optimal for an arbitrary packet drop pattern. Further, the solution is appealing from a practical point of view because it can be implemented as a small modification of an existing LQG control design
Dynamic Rate Adaptation for Improved Throughput and Delay in Wireless Network Coded Broadcast
In this paper we provide theoretical and simulation-based study of the
delivery delay performance of a number of existing throughput optimal coding
schemes and use the results to design a new dynamic rate adaptation scheme that
achieves improved overall throughput-delay performance.
Under a baseline rate control scheme, the receivers' delay performance is
examined. Based on their Markov states, the knowledge difference between the
sender and receiver, three distinct methods for packet delivery are identified:
zero state, leader state and coefficient-based delivery. We provide analyses of
each of these and show that, in many cases, zero state delivery alone presents
a tractable approximation of the expected packet delivery behaviour.
Interestingly, while coefficient-based delivery has so far been treated as a
secondary effect in the literature, we find that the choice of coefficients is
extremely important in determining the delay, and a well chosen encoding scheme
can, in fact, contribute a significant improvement to the delivery delay.
Based on our delivery delay model, we develop a dynamic rate adaptation
scheme which uses performance prediction models to determine the sender
transmission rate. Surprisingly, taking this approach leads us to the simple
conclusion that the sender should regulate its addition rate based on the total
number of undelivered packets stored at the receivers. We show that despite its
simplicity, our proposed dynamic rate adaptation scheme results in noticeably
improved throughput-delay performance over existing schemes in the literature.Comment: 14 pages, 15 figure
Advanced Fade Countermeasures for DVB-S2 Systems in Railway Scenarios
This paper deals with the analysis of advanced fade countermeasures for supporting DVB-S2 reception by mobile terminals mounted on high-speed trains. Recent market studies indicate this as a potential profitable market for satellite communications, provided that integration with wireless terrestrial networks can be implemented to bridge the satellite connectivity inside railway tunnels and large train stations. In turn, the satellite can typically offer the coverage of around 80% of the railway path with existing space infrastructure. This piece of work, representing the first step of a wider study, is focusing on the modifications which may be required in the DVB-S2 standard (to be employed in the forward link) in order to achieve reliable reception in a challenging environment such as the railway one. Modifications have been devised trying to minimize the impact on the existing air interface, standardized for fixed terminals
Network coding for transport protocols
With the proliferation of smart devices that require Internet connectivity anytime, anywhere, and the recent technological
advances that make it possible, current networked systems will have to provide a various range of services, such as content
distribution, in a wide range of settings, including wireless environments. Wireless links may experience temporary losses,
however, TCP, the de facto protocol for robust unicast communications, reacts by reducing the congestion window drastically
and injecting less traffic in the network. Consequently the wireless links are underutilized and the overall performance of the
TCP protocol in wireless environments is poor. As content delivery (i.e. multicasting) services, such as BBC iPlayer, become
popular, the network needs to support the reliable transport of the data at high rates, and with specific delay constraints. A
typical approach to deliver content in a scalable way is to rely on peer-to-peer technology (used by BitTorrent, Spotify and
PPLive), where users share their resources, including bandwidth, storage space, and processing power. Still, these systems
suffer from the lack of incentives for resource sharing and cooperation, and this problem is exacerbated in the presence of
heterogenous users, where a tit-for-tat scheme is difficult to implement.
Due to the issues highlighted above, current network architectures need to be changed in order to accommodate the usersÂż
demands for reliable and quality communications. In other words, the emergent need for advanced modes of information
transport requires revisiting and improving network components at various levels of the network stack.
The innovative paradigm of network coding has been shown as a promising technique to change the design of networked
systems, by providing a shift from how data flows traditionally move through the network. This shift implies that data flows are
no longer kept separate, according to the Âżstore-and-forwardÂż model, but they are also processed and mixed in the network. By
appropriately combining data by means of network coding, it is expected to obtain significant benefits in several areas of
network design and architecture.
In this thesis, we set out to show the benefits of including network coding into three communication paradigms, namely point-topoint
communications (e.g. unicast), point-to-multipoint communications (e.g. multicast), and multipoint-to-multipoint
communications (e.g. peer-to-peer networks). For the first direction, we propose a network coding-based multipath scheme and
show that TCP unicast sessions are feasible in highly volatile wireless environments. For point-to-multipoint communications,
we give an algorithm to optimally achieve all the rate pairs from the rate region in the case of degraded multicast over the
combination network. We also propose a system for live streaming that ensures reliability and quality of service to heterogenous
users, even if data transmissions occur over lossy wireless links. Finally, for multipoint-to-multipoint communications, we design
a system to provide incentives for live streaming in a peer-to-peer setting, where users have subscribed to different levels of
quality.
Our work shows that network coding enables a reliable transport of data, even in highly volatile environments, or in delay
sensitive scenarios such as live streaming, and facilitates the implementation of an efficient incentive system, even in the
presence of heterogenous users. Thus, network coding can solve the challenges faced by next generation networks
in order to support advanced information transport.Postprint (published version
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