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

In energy detection for cognitive radio spectrum sensing, the noise variance is usually assumed given, by which a threshold is set to guarantee a desired constant false alarm rate (CFAR) or a constant detection rate (CDR). However, in practical situations, the exact information of noise variance is generally unavailable to a certain extent due to the fact that the total noise consists of time-varying thermal noise, receiver noise, and environmental noise, etc. Hence, setting the thresholds by using an estimated noise variance may result in different false alarm probabilities from the desired ones. In this paper, we analyze the basic statistical properties of the false alarm probability by using estimated noise variance, and propose a method to obtain more suitable CFAR thresholds for energy detection. Specifically, we first come up with explicit descriptions on the expectations of the resultant probability, and then analyze the upper bounds of their variance. Based on these theoretical preparations, a new method for precisely obtaining the CFAR thresholds is proposed in order to assure that the expected false alarm probability can be as close to the predetermined as possible. All analytical results derived in this paper are testified by corresponding numerical experiments.

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Statistical Properties of Energy Detection for Spectrum Sensing by Using Estimated Noise Variance

The paper considers the problem of single-link failure localization in all-optical mesh networks. Our study follows a generic monitoring approach using supervisory lightpaths (S-LPs), in which a set of bi-directional monitoring trails (bm-trails) are defined and closely monitored, such that the network controller can achieve unambiguous failure localization (UFL) for any single link by collecting the flooded alarms from the affected bm-trails. With a target of minimizing the number of bm-trails (or the length of alarm codes) required for single-link UFL, the paper provides optimal (or essentially optimal) solutions to the bm-trail allocation problem on a number of well known topologies. First we demonstrate that the theoretical lower bound of [log2 (|E|+1)] bm-trails can be achieved in any 2 · [{ log2 {(|E|+1)} }] connected graph, where |E| is the number of links. Next, we prove an essentially optimal solution for 1-by-N grid topologies (also known as chocolate bar graphs), where [{0.42+ log2{(|E|+2)}}] bm-trails can be achieved. Based on the solution for chocolate bars, we further investigate bm-trail solutions to general 2-dimensional (2D) grid topologies, and the developed solution requires no more than 3+[ log2 (|E|+1)] bm-trails for UFL. Such an optimal (or essentially optimal) logarithmic behavior, although has been well observed in general topologies in our previous studies , is formalized for the first time in this paper via a suite of polynomial-time deterministic constructions that consume less than a few seconds of running time in topologies of thousands of nodes.

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Link Fault Localization Using Bi-Directional M-Trails in All-Optical Mesh Networks

This paper investigates the joint user scheduling (US) and user association (UA) problem for OFDMA-based networks under the centralized radio access network (C-RAN) architecture. We first formulate the joint optimization problem for US and UA, which is intractable in its exact form, and therefore, we propose a corresponding upper bound problem, with much lower computational complexity, with the help of a novel continuous rate function. We show that the upper bound problem can be further converted into an equivalent convex optimization problem via geometric programming (GP) that can be solved with inter-baseband unit coordination, which is viable in the C-RAN architecture. Furthermore, we show that the solutions of the convex upper bound problem can be mapped into the solution space of the original joint US and UA problem with a small gap. As a practically implementable solution to the original problem, a heuristic-based scheduler has been developed to obtain quasi-optimal UA and US solutions for the uplink (UL) as well as the downlink (DL) transmissions. Through extensive numerical simulations, we verify that the performance of the proposed heuristic-based scheduler is quasi-optimal on both UL and DL.

Joint User Scheduling and RRU Association for ODFMA-Based Networks With Inter-BBU Coordination

In this paper, we study the performance of the cumulative Automatic Repeat reQuest (ARQ) in IEEE 802.16 networks. An analytical model is developed to investigate some important performance metrics, such as protocol data unit (PDU) delivery delay, service data unit (SDU) delivery delay, and goodput. A general scheduling scheme and the flexible retransmission of lost PDUs are jointly considered in the analytical model, which provides a more valuable and practical guideline for the system design and performance evaluation. Extensive simulations are conducted to demonstrate the impacts of different operational parameters on the performance metrics and verify the accuracy of the analytical model.

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Performance analysis of the cumulative ARQ in IEEE 802.16 networks

In ad hoc cognitive radio (CR) networks, channel negotiation and access have been raised as challenging issues due to its highly dynamic nature and strong user diversity, particularly in situations where a dedicated common control channel is not reserved among the distributed CR nodes. In this paper, a novel stochastic channel negotiation algorithm is proposed for improving spectrum sharing efficiency in the CR networks. The paper first formulates the problem of channel selection for negotiation, aiming to maximize the probability of successful channel negotiation. The formulated optimization problem is then solved using a dynamic Markov-Chain Monte-Carlo (MCMC) scheme. Simulation is conducted to examine the performance of the proposed approach and demonstrate its merits. We have witnessed that the proposed approach can serve as an excellent complementary to the CR networks in which dedicated control channels are not defined.

Pin-Han Ho

Papers

Statistical Properties of Energy Detection for Spectrum Sensing by Using Estimated Noise Variance

Link Fault Localization Using Bi-Directional M-Trails in All-Optical Mesh Networks

Joint User Scheduling and RRU Association for ODFMA-Based Networks With Inter-BBU Coordination

Performance analysis of the cumulative ARQ in IEEE 802.16 networks

Dynamic Markov-Chain Monte Carlo Channel Negotiation for Cognitive Radio