Suzan Bayhan

Cognitive femtocell networks: an overlay architecture for localized dynamic spectrum access [Dynamic Spectrum Management]

We define and propose a femtocell-based cognitive radio architecture for enabling multitiered opportunistic access in next-generation broadband wireless systems. This architecture combines the conventional femtocell idea with an infrastructure-based overlay cognitive network paradigm. The cognitive femtocell concept leads to simpler and easier proliferation of cognitive radio into practical systems. We highlight the drawbacks and advantages of the proposed network structure with a discussion on research directions for cognitive femtocell architecture. We also provide experimental results to illustrate a general proof of concept for this new modality.

Radio environment map as enabler for practical cognitive radio networks

Latest regulations on TV white space communications and emerging trends of spectrum access through geolocation databases relax the regulatory constraints on Cognitive Radios (CRs). Geolocation databases are designed to store information related to incumbents, and CRs are envisioned to consult this database before spectrum access. Spectrum occupancy and related environment information can be constructed using these geolocation databases. In that regard, Radio Environment Map (REM) is a promising tool that provides a practical means for the realization of cognitive radio networks (CRNs). It constructs a comprehensive map of the CRN by utilizing multi-domain information from geolocation databases, characteristics of spectrum use, geographical terrain models, propagation environment, and regulations. REMs contribute to cognition engines by building long-term knowledge via processing spectrum measurements collected from sensors to estimate the state of locations where there is no measurement data. In addition, REM utilizes feedback from the CRs and can apply various learning tools. The vision is to design CRNs such that CRs, though being simple devices without advanced cognitive functionalities, can become cognitive via REMs and operate in an efficient manner. In this paper, an overview of the REM concept is presented in various dimensions ranging from its architecture and stored information to REM construction techniques as well as REM quality metrics.

Energy-Efficient Multichannel Cooperative Sensing Scheduling With Heterogeneous Channel Conditions for Cognitive Radio Networks

Spectrum sensing is an important aspect of cognitive radio networks (CRNs). Secondary users (SUs) should periodically sense the channels to ensure primary-user (PU) protection. Sensing with cooperation among several SUs is more robust and less error prone. However, cooperation also increases the energy spent for sensing. Considering the periodic nature of sensing, even a small amount of savings in each sensing period leads to considerable improvement in the long run. In this paper, we consider the problem of energy-efficient (EE) spectrum sensing scheduling with satisfactory PU protection. Our model exploits the diversity of SUs in their received signal-to-noise ratio (SNR) of the primary signal to determine the sensing duration for each user/channel pair for higher energy efficiency. We model the given problem as an optimization problem with two different objectives. The first objective is to minimize the energy consumption, and the second objective is to minimize the spectrum sensing duration to maximize the remaining time for data transmission. We solve both problems using the outer linearization method. In addition, we present two suboptimal but efficient heuristic methods. We provide an extensive performance analysis of our proposed methods under various numbers of SUs, average channel SNR, and channel sampling frequency. Our analysis reveals that all proposals with an energy minimization perspective provide significant energy savings compared with a pure transmission-time maximization (TXT) technique.

A Markovian approach for best-fit channel selection in cognitive radio networks

An efficient channel selection scheme in multi-user cognitive radio networks (CRN) is supposed to address two often conflicting objectives: enhancing the network-wide performance while satisfying the individual quality of service demands of cognitive radios (CRs). In this sense, best-fit channel selection (BFC) inspired from well-known classical bin-packing algorithms achieves better performance compared to the longest-idle time channel selection (LITC). BFC facilitates each CR, with the capability of primary channel idle time estimation, select the channel that is expected to be idle for sufficiently long duration for its traffic request. Unlike BFC, LITC favors the selection of the channel with the longest idle time although the channel is not needed and will not be used for such long duration by this CR. As a generalization of these two approaches, we introduce the p - selfish scheme in which a CR selects the longest channel with probability p. Hence, we also refer to p as degree of selfishness. In [1], we evaluate the performance of BFC and show that it improves performance of the CRN in terms of spectrum opportunity utilization and CR throughput, compared to the LITC. In this work, we present an analytic model for BFC using continuous-time Markov chains (CTMC). The performance improvement achieved by BFC is due the reduced spectrum fragmentation that is achieved by best-fit allocation. BFC can be considered as an implicit solution to spectrum fragmentation in time dimension. We study the CR performance in terms of spectrum opportunity utilization and probability of success under various degree of selfishness through the presented model and compare our results with the simulation results.

Distributed channel selection in CRAHNs: A non-selfish scheme for mitigating spectrum fragmentation

In this paper, we consider the problem of spectrum sharing in CRAHNs and propose a distributed channel selection scheme. The key functionality of our proposal, best-fit channel selection (BFC) is that it accounts both the primary channel traffic activity and CR traffic activity in channel selection. We assume CR nodes have the capability of estimating the primary channel traffic activities. In BFC, each CR selects a channel among the primary user (PU) channels for transmission that best fits to its transmission time requirement. We compare the performance of BFC to the widely known longest idle time channel selection (LITC) scheme. In LITC, a CR selects the channel that has the longest expected idle time independent of its transmission needs. In a multi-user CRN, this may degrade the network performance compared to the non-selfish BFC approach. LITC is considered selfish since each CR aims to maximize its own benefit and thus wastes resources that may be utilized by other nodes in the network. BFC providing an efficient spectrum sharing mechanism implicitly mitigates the effect of spectrum fragmentation which is a significant issue degrading the CR spectrum utilization. In CRNs, spectrum may be fragmented in various dimensions, e.g. time and frequency, such that some parts of the spectrum can not be used although being idle. Our proposal provides a solution to the spectrum fragmentation issue in time dimension at the medium access control (MAC) layer. By a set of simulations, we highlight the performance improvement by BFC over the conventional LITC under various CR/PU traffic, number of CRs, estimation accuracy and buffering capability. Simulation results show that the performance of the proposed BFC is significantly superior to that of LITC in terms of probability of successful transmission, spectrum opportunity utilization and fragmentation.

Effects of Cooperation Policy and Network Topology on Performance of In-Network Caching

In-network caching is a key component in information-centric networking. In this paper we show that there is a tradeoff between two common caching metrics, byte hit rate and footprint reduction, and show that a cooperation policy can adjust this tradeoff. We model the cooperation policy with only two parameters - search radius r and number of copies in the network K. These two parameters represent the range of cooperation and tolerance of duplicates. We show how cooperation policy impacts content distribution, and further illustrate the relation between content popularity and topological properties. Our work leads many implications on how to take advantage of topological properties in in-network caching strategy design.

Optimal chunking and partial caching in information-centric networks

Caching is widely used to reduce network traffic and improve user experience. Traditionally caches store complete objects, but video files and the recent emergence of information-centric networking have highlighted a need for understanding how partial caching could be beneficial. In partial caching, objects are divided into chunks which are cached either independently or by exploiting common properties of chunks of the same file. In this paper, we identify why partial caching is beneficial, and propose a way to quantify the benefit. We develop an optimal n-Chunking algorithm with complexity O ( ns 2 ) for an s-byte file, and compare it with ? -optimal homogeneous chunking, where ? is bounded by O ( n - 2 ) . Our analytical results and comparison lead to the surprising conclusion that neither sophisticated partial caching algorithm nor high complexity optimal chunking are needed in information-centric networks. Instead, simple utility-based in-network caching algorithm and low complexity homogeneous chunking are sufficient to achieve the most benefits of partial caching.

A novel handover protocol to prevent hidden node problem in satellite assisted cognitive radio networks

The rapid growth in wireless technologies has intensified the demand for the radio spectrum. On the other hand, the research studies reveal that the spectrum utilization is unevenly distributed, which leads to the conclusion that there is a problem with the spectrum management and allocation rather than the scarcity of the spectrum itself. This inefficiency in spectrum usage in addition to the escalating demand for the radio spectrum fostered the research studies that focus on new communication paradigms referred to as dynamic spectrum access (DSA) and cognitive radio networks, which are based on opportunistically utilizing the radio spectrum. IEEE 802.22 is the first standard for cognitive radio networks, in which, however, network entry and initialization, as well as the hidden incumbent problem have not yet completely been addressed. On the other hand, mobility is also an unexplored issue in cognitive radio networks. In this paper, we propose a novel protocol that combats the hidden incumbent problem during network entry, initialization and handover, while at the same time taking the mobility pattern of the cognitive devices into consideration. Our proposed scheme is based on a satellite assisted cognitive radio architecture. Our model outperforms the current IEEE 802.22 scheme and other work in the literature in terms of connection setup delay.

Energy efficiency is a subtle concept: fundamental trade-offs for cognitive radio networks

This article discusses the implications of facilitating higher energy efficiency in cognitive radio networks from the perspective of fundamental trade-offs (i.e, what needs to be sacrificed to be energy-efficient). These trade-offs are identified as QoS, fairness, PU interference, network architecture, and security, which are also essential network design dimensions. We analyze these dimensions and their interactions focusing on energy efficiency. Furthermore, future research directions related to the integration of CRN with other networking paradigms and energy efficiency are introduced and discussed.

Effect of social relations on cooperative sensing in cognitive radio networks

Previous works in cognitive radio networks (CRNs) have shown that cooperation in sensing improves sensing reliability and in turn enhances the network throughput. However, the cooperative behavior is accepted as the default mode of operation, which may not always hold. In this work, we loose this assumption and introduce a cooperative mode of operation conditioned on social relations between Cognitive Radios (CRs). Rather than taking CRs as wireless devices with no context, we associate each CR with its user that has some social relations, e.g. friendship, community, selfishness. Using these relations among CRs, we propose a social-aware cooperative sensing scheme and analyze its effects on sensing performance. We believe that exploiting social metrics assists cooperative sensing in CRNs and a model with social relations embedded will fit better to the next decades networking paradigm.