Wireless Communications

An Integrated Agent Architecture for Software Defined Radio. Rapid-prototype cognitive radio, CR1, was developed to apply these.The modern software defined radio has been called the heart of a cognitive radio. Cognitive radio: an integrated agent architecture for software defined radio. Http:bwrc.eecs.berkeley.eduResearchMCMACR White paper final1.pdf. The cognitive radio, built on a software-defined radio, assumes. Radio: An Integrated Agent Architecture for Software Defined Radio, Ph.D. The need for software-defined radios is underlined and the most important notions used for such. Mitola III, Cognitive radio: an integrated agent architecture for software defined radio, Ph.D. This results in the set-theoretic ontology of radio knowledge defined in the. Cognitive Radio An Integrated Agent Architecture for Software.This article first briefly reviews the basic concepts about cognitive radio CR. Cognitive Radio-An Integrated Agent Architecture for Software Defined Radio. Cognitive Radio RHMZ 2007. Software-defined radio SDR idea 1. Cognitive radio: An integrated agent architecture for software.Cognitive Radio SOFTWARE DEFINED RADIO, AND ADAPTIVE WIRELESS SYSTEMS2 Cognitive Networks. 3 Joseph Mitola III, Cognitive Radio: An Integrated Agent Architecture for Software Defined Radio Stockholm.

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Cognitive Radio An Integrated Agent Architecture for Software Defined Radio

Mobile ad hoc networks (MANETs) represent complex distributed systems that comprise wireless mobile nodes that can freely and dynamically self-organize into arbitrary and temporary, ‘‘ad-hoc’’ network topologies, allowing people and devices to seamlessly internetwork in areas with no pre-existing communication infrastructure, e.g., disaster recovery environments. Ad hoc networking concept is not a new one, having been around in various forms for over 20 years. Traditionally, tactical networks have been the only communication networking application that followed the ad hoc paradigm. Recently, the introduction of new technologies such as the Bluetooth, IEEE 802.11 and Hyperlan are helping enable eventual commercial MANET deployments outside the military domain. These recent evolutions have been generating a renewed and growing interest in the research and development of MANET. This paper attempts to provide a comprehensive overview of this dynamic field. It first explains the important role that mobile ad hoc networks play in the evolution of future wireless technologies. Then, it reviews the latest research activities in these areas, including a summary of MANETs characteristics, capabilities, applications, and design constraints. The paper concludes by presenting a set of challenges and problems requiring further research in the future. � 2003 Elsevier B.V. All rights reserved.

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Mobile ad hoc networking: imperatives and challenges

A cost aware metric for wireless networks based on remaining battery power at nodes was proposed for shortest-cost routing algorithms, assuming constant transmission power. Power-aware metrics, where transmission power depends on distance between nodes and corresponding shortest power algorithms were also proposed. We define a power-cost metric based on the combination of both node's lifetime and distance-based power metrics. We investigate some properties of power adjusted transmissions and show that, if additional nodes can be placed at desired locations between two nodes at distance d, the transmission power can be made linear in d as opposed to d/sup /spl alpha// dependence for /spl alpha/ /spl ges/ 2. This provides basis for power, cost, and power-cost localized routing algorithms where nodes make routing decisions solely on the basis, of location of their neighbors and destination. The power-aware routing algorithm attempts to minimize the total power needed to route a message between a source and a destination. The cost-aware routing algorithm is aimed at extending the battery's worst-case lifetime at each node. The combined power-cost localized routing algorithm attempts to minimize the total power needed and to avoid nodes with a short battery's remaining lifetime. We prove that the proposed localized power, cost, and power-cost efficient routing algorithms are loop-free and show their efficiency by experiments.

Power-aware localized routing in wireless networks

We introduce a resource reservation-based routing and signaling algorithm, Ad hoc Qos on-demand routing (AQOR), that provides end-to-end quality of service (QoS) support, in terms of bandwidth and end-to-end delay, in mobile ad hoc networks (MANETs). The increasing use of MANETs for transferring multimedia applications such as voice, video and data, leads to the need to provide QoS support. To perform accurate admission control and resource reservation in AQOR, we have developed detailed computations that allow us to estimate the available bandwidth and end-to-end delay in unsynchronized wireless environment. AQOR also includes efficient mechanisms for QoS maintenance, including temporary reservation and destination-initiated recovery processes. The performance of AQOR is studied in detail by simulation using OPNET Modeler. The results validate that AQOR provides QoS support in ad hoc wireless networks with high reliability and low overhead.

Ad hoc QoS on-demand routing (AQOR) in mobile ad hoc networks

The emergence of nomadic applications have generated much interest in wireless network infrastructures that support real-time communications. We propose a bandwidth routing protocol for quality-of-service (QoS) support in a multihop mobile network. The QoS routing feature is important for a mobile network to interconnect wired networks with QoS support (e.g., ATM, Internet, etc.). The QoS routing protocol can also work in a stand-alone multihop mobile network for real-time applications. This QoS routing protocol contains end-to-end bandwidth calculation and bandwidth allocation. Under such a routing protocol, the source (or the ATM gateway) is informed of the bandwidth and QoS available to any destination in the mobile network. This knowledge enables the establishment of QoS connections within the mobile network and the efficient support of real-time applications. In addition, it enables more efficient call admission control. In the case of ATM interconnection, the bandwidth information can be used to carry out intelligent handoff between ATM gateways and/or to extend the ATM virtual circuit (VC) service to the mobile network with possible renegotiation of QoS parameters at the gateway. We examine the system performance in various QoS traffic flows and mobility environments via simulation. Simulation results suggest distinct performance advantages of our protocol that calculates the bandwidth information. It is particularly useful in call admission control. Furthermore, "standby" routing enhances the performance in the mobile environment. Simulation experiments show this improvement.

https://ir.nctu.edu.tw:443/bitstream/11536/31180/1/000081909000009.pdf

QoS routing in ad hoc wireless networks

Future wireless networks promise immense increases on data rate and energy efficiency while overcoming the difficulties of charging the wireless stations or devices in the Internet of Things (IoT) with the capability of simultaneous wireless information and power transfer (SWIPT). For such networks, jointly optimizing beamforming, power control, and energy harvesting to enhance the communication performance from the base stations (BSs) (or access points (APs)) to the mobile nodes (MNs) served would be a real challenge. In this work, we formulate the joint optimization as a mixed integer nonlinear programming (MINLP) problem, which can be also realized as a complex multiple resource allocation (MRA) optimization problem subject to different allocation constraints. By means of deep reinforcement learning to estimate future rewards of actions based on the reported information from the users served by the networks, we introduce single-layer MRA algorithms based on deep Q-learning (DQN) and deep deterministic policy gradient (DDPG), respectively, as the basis for the downlink wireless transmissions. Moreover, by incorporating the capability of data-driven DQN technique and the strength of noncooperative game theory model, we propose a two-layer iterative approach to resolve the NP-hard MRA problem, which can further improve the communication performance in terms of data rate, energy harvesting, and power consumption. For the two-layer approach, we also introduce a pricing strategy for BSs or APs to determine their power costs on the basis of social utility maximization to control the transmit power. Finally, with the simulated environment based on realistic wireless networks, our numerical results show that the two-layer MRA algorithm proposed can achieve up to 2.3 times higher value than the single-layer counterparts which represent the data-driven deep reinforcement learning-based algorithms extended to resolve the problem, in terms of the utilities designed to reflect the trade-off among the performance metrics considered.

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Joint Beamforming, Power Allocation, and Splitting Control for SWIPT-Enabled IoT Networks with Deep Reinforcement Learning and Game Theory

The emergence of nomadic applications have generated a lot of interest in wireless network infrastructures which support multimedia services. We propose a bandwidth routing algorithm for multimedia support in a multihop wireless network. This network can be interconnected to wired networks (e.g. ATM or Internet) or stand alone. Our bandwidth routing includes bandwidth calculation and reservation schemes. Under such a routing algorithm, we can derive a route to satisfy the bandwidth requirement for the QoS constraint. At a source node, the bandwidth information can be used to decide to accept a new call or not immediately. This is specially important to carry out a fast handoff when interconnecting to an ATM backbone infrastructure. It enables an efficient call admission control. The simulation results show that the bandwidth routing algorithm is very useful in extending the ATM virtual circuit service to the wireless network. Different types of QoS traffic can be integrated in such a dynamic radio network with high performance.

http://ieeexplore.ieee.org/iel5/6295/16830/00775981.pdf

Jain-Shing Liu

Papers

QoS routing in ad hoc wireless networks

Joint Beamforming, Power Allocation, and Splitting Control for SWIPT-Enabled IoT Networks with Deep Reinforcement Learning and Game Theory

Bandwidth routing in ad hoc wireless networks

Bandwidth Routing in Ad Hoc Wireless Networks

Grayscale image coding using optimal pixel grouping and adaptive multi-grouping division block truncation coding