Cooperative spectrum sensing in cognitive radio networks: A survey

This document provides updates to IEEE Std 802.16's MIB for the MAC, PHY and asso- ciated management procedures in order to accommodate recent extensions to the standard.

IEEE Standard for Local and Metropolitan Area Networks Part 16: Air Interface for Fixed Broadband Wireless Access Systems Draft Amendment: Management Information Base Extensions

The Transmission Control Protocol.

With the rapid deployment of new wireless devices and applications, the last decade has witnessed a growing demand for wireless radio spectrum. However, the fixed spectrum assignment policy becomes a bottleneck for more efficient spectrum utilization, under which a great portion of the licensed spectrum is severely under-utilized. The inefficient usage of the limited spectrum resources urges the spectrum regulatory bodies to review their policy and start to seek for innovative communication technology that can exploit the wireless spectrum in a more intelligent and flexible way. The concept of cognitive radio is proposed to address the issue of spectrum efficiency and has been receiving an increasing attention in recent years, since it equips wireless users the capability to optimally adapt their operating parameters according to the interactions with the surrounding radio environment. There have been many significant developments in the past few years on cognitive radios. This paper surveys recent advances in research related to cognitive radios. The fundamentals of cognitive radio technology, architecture of a cognitive radio network and its applications are first introduced. The existing works in spectrum sensing are reviewed, and important issues in dynamic spectrum allocation and sharing are investigated in detail.

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Advances in cognitive radio networks: A survey

Intelligent reflecting surface (IRS) is an enabling technology to engineer the radio signal propagation in wireless networks. By smartly tuning the signal reflection via a large number of low-cost passive reflecting elements, IRS is capable of dynamically altering wireless channels to enhance the communication performance. It is thus expected that the new IRS-aided hybrid wireless network comprising both active and passive components will be highly promising to achieve a sustainable capacity growth cost-effectively in the future. Despite its great potential, IRS faces new challenges to be efficiently integrated into wireless networks, such as reflection optimization, channel estimation, and deployment from communication design perspectives. In this paper, we provide a tutorial overview of IRS-aided wireless communications to address the above issues, and elaborate its reflection and channel models, hardware architecture and practical constraints, as well as various appealing applications in wireless networks. Moreover, we highlight important directions worthy of further investigation in future work.

Intelligent Reflecting Surface-Aided Wireless Communications: A Tutorial

Emerging 4G standards, such as WiMAX, LTE, and TD-SCDMA, have adopted the proven technique of Adaptive Modulation and Coding (AMC) to dynamically react to channel ﬂuctuations while maintaining bit- error rate targets of the transmission. To mitigate the vicious effects due to stale channel state indication (CSI) problem, this paper introduces a novel framework by incorporating AMC with layered transmission through Superposition Coding (SPC). A Markov chain model is adopted under this framework, to effectively assist the system in selecting the optimal modulation and coding scheme for each layer in every multi-resolution unicast transmission. Extensive simulation is conducted to verify the proposed framework and compare it with a number of counterparts. The results demonstrate that the proposed framework can achieve a much better spectrum efﬁciency due to improved robustness by addressing the stale CSI problem at each multi-resolution modulated transmission.

Layered Adaptive Modulation and Coding for 4G Wireless Networks

Maximizing the optical network unit's (ONU) sleep time is an effective approach for achieving maxi- mum energy conservation in green Ethernet passive optical networks (EPONs). While overlapping downstream and upstream ONU transmissions can maximize the ONU sleep time, it jeopardizes the quality of service (QoS) performance of the network, especially for downstream traffic in case the overlapping is based on the upstream time slot. In this paper, we study the downstream traffic performance in green EPONs under the limited service discipline and the upstream-based overlapped time window. Specifically, we first derive the expected mean packet delay, and then present a closed-form expression of the ONU sleep time, setting identical upstream/downstream transmission cycle times based on a maximum downstream traffic delay re- quirement. With the proposed system model, we present a novel downstream bandwidth allocation scheme for energy conservation in green EPONs. Simulation results verify the proposed model and highlight the advantages of our scheme over conventional approaches.

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Downstream-based Scheduling for Energy Conservation in Green EPONs

To extend the functional lifetime of battery-operated Wireless Sensor Networks (WSNs), stringent sleep scheduling strategies with communication duty cycles running at sub-1% range are expected to be adopted. Although ultra-low communication duty cycles can cast a detrimental impact on sensing coverage and network connectivity, its effects can be mitigated with adaptive sleep scheduling, node deployment redundancy and multipath routing within the mesh WSN topology. Prior research on this issue had led to the proposal of a new design paradigm called Sense-Sleep Tree (SS-Tree). The SS-Tree aims to harmonise the various engineering issues and provides a method to increase the monitoring coverage and the operational lifetime of mesh-based WSNs engaged in wide-area event-driven surveillance applications. This paper further expands and refines the SS-Tree approach by incorporating practical design considerations such as transmission range assignment, duty cycling and sensing coverage. This approach can achieve higher energy efficiency and satisfy various application requirements during WSN network planning and predeployment phase.

http://bbcr.uwaterloo.ca/~xshen/paper/2006/pre-osswtr.pdf

Optimal sleep scheduling with transmission range assignment in application-specific wireless sensor networks

We consider traffic scheduling in performance guaranteed switches with optical fabrics to ensure 100% throughput and bounded packet delay. Each switch reconfiguration consumes a constant period of time called reconfiguration overhead, during which no packet can be transmitted across the switch. To minimize the packet delay bound for an arbitrary traffic matrix, the number of switch configurations in the schedule should be no larger than the switch size N . This is called minimum delay scheduling, where the ideal minimum packet delay bound is determined solely by the total overhead of the N switch reconfigurations. A speedup in the switch determines the actual packet delay bound, which decreases toward the ideal bound as the speedup increases. Our objective is to minimize the required speedup S schedule under a given actual packet delay bound. We propose a novel minimum delay scheduling algorithm quasi largest-entry-first (QLEF) to solve this problem. Compared with the existing minimum delay scheduling algorithms MIN and alphai-SCALE, QLEF dramatically cuts down the required S schedule bound. For example, QLEF only requires S schedule=17.89 for N=450, whereas MIN and alphai -SCALE require S schedule=37.13 and 27.82, respectively. This gives a significant performance gain of 52% over MIN and 36% over alphai-SCALE.

https://lib-repos.fun.ac.jp/dspace/bitstream/10445/5309/2/jiang_2009-9-IEEEJLT.pdf

Minimum Delay Scheduling for Performance Guaranteed Switches With Optical Fabrics

We consider power allocation in OFDM based underlay cognitive radio networks with partially known inter-system CSI (Channel State Information). Under a given total transmit power limit at the SU (Secondary User) transmitter, the goal is to assign a certain amount of power for signal transmission in each OFDM sub-channel, such that the SU's overall throughput can be maximized, and the average interference to the PU can be kept within a target outage probability level. The existing algorithm adopts an iterative binary searching process to find the solution, where the classic Water-Filling (WF) is invoked in each loop, which needs a relatively long running time. In this paper, an efficient algorithm is proposed to solve the problem in a much simpler and faster way. Specifically, we first propose an efficient approach to implement WF based on some in-depth theoretical analysis. Then, a novel power allocation algorithm is proposed by removing the binary searching process. Our algorithm runs WF only once and then directly calculates the final solution. Numerical results show that it can run tens to hundreds times faster than the existing algorithms, depending on the total number of OFDM sub-channels.

Pin-Han Ho

Papers

Layered Adaptive Modulation and Coding for 4G Wireless Networks

Downstream-based Scheduling for Energy Conservation in Green EPONs

Optimal sleep scheduling with transmission range assignment in application-specific wireless sensor networks

Minimum Delay Scheduling for Performance Guaranteed Switches With Optical Fabrics

An Efficient Power Allocation Algorithm for OFDM Based Underlay Cognitive Radio Networks