Survey on coexistence of heterogeneous wireless networks in 2.4 GHz and TV white spaces <s> Introduction <s> Software radios are emerging as platforms for multiband multimode personal communications systems. Radio etiquette is the set of RF bands, air interfaces, protocols, and spatial and temporal patterns that moderate the use of the radio spectrum. Cognitive radio extends the software radio with radio-domain model-based reasoning about such etiquettes. Cognitive radio enhances the flexibility of personal services through a radio knowledge representation language. This language represents knowledge of radio etiquette, devices, software modules, propagation, networks, user needs, and application scenarios in a way that supports automated reasoning about the needs of the user. This empowers software radios to conduct expressive negotiations among peers about the use of radio spectrum across fluents of space, time, and user context. With RKRL, cognitive radio agents may actively manipulate the protocol stack to adapt known etiquettes to better satisfy the user's needs. This transforms radio nodes from blind executors of predefined protocols to radio-domain-aware intelligent agents that search out ways to deliver the services the user wants even if that user does not know how to obtain them. Software radio provides an ideal platform for the realization of cognitive radio. <s> BIB001 </s> Survey on coexistence of heterogeneous wireless networks in 2.4 GHz and TV white spaces <s> Introduction <s> As more and more wireless devices use the 2.4 GHz radio spectrum, the coexistence of 2.4 GHz wireless devices operating in one place has become a hot topic. With low transmit power, the widely deployed IEEE 802.15.4-based networks are easily interfered with by other 2.4 GHz wireless networks, such as IEEE 802.11. IEEE 802.15.4-based wireless networks have paid great attention to the coexistence between themselves and with other non-IEEE 802.15.4 wireless networks. This problem has been further promoted by two new industry wireless standards, WirelessHART and ISA100, to meet special industry requirements. This paper surveys the studies on the coexistence between IEEE 802.11 and IEEE 802.15.4-based networks following the general analysis method of “question-analysis-solution.” Based on the survey study, we discuss about some open research issues and developments in this field. <s> BIB002 </s> Survey on coexistence of heterogeneous wireless networks in 2.4 GHz and TV white spaces <s> Introduction <s> With the development of dynamic spectrum access technologies, such as cognitive radio, the secondary use of underutilized TV broadcast spectrum has come a step closer to reality. Recently, a number of wireless standards that incorporate CR technology have been finalized or are being developed to standardize systems that will coexist in the same TV white spaces. In these wireless standards, the widely studied problem of primary-secondary network coexistence has been addressed by the use of incumbent geolocation databases augmented with spectrum sensing techniques. However, the challenging problem of secondary-secondary coexistence?in particular, heterogeneous secondary coexistence- has garnered much less attention in the standards and related literature. The coexistence of heterogeneous secondary networks poses challenging problems due to a number of factors, including the disparity of PHY/MAC strategies of the coexisting systems. In this article, we discuss the mechanisms that have been proposed for heterogeneous coexistence, and propose a taxonomy of those mechanisms targeting TVWSs. Through this taxonomy, our aim is to offer a clear picture of the heterogeneous coexistence issues and related technical challenges, and shed light on the possible solution space. <s> BIB003 </s> Survey on coexistence of heterogeneous wireless networks in 2.4 GHz and TV white spaces <s> Introduction <s> Cognitive radio (CR) technologies have led to several wireless standards (e.g., IEEE 802.11af and IEEE 802.22) that enable secondary networks to access the TV white-space (TVWS) spectrum. Different unlicensed wireless technologies with different PHY/MAC designs are expected to coexist in the same TVWS spectrum-we refer to such a situation as heterogeneous coexistence. The heterogeneity of the PHY/MAC designs of coexisting CR networks can potentially exacerbate the hidden terminal problem. This problem cannot be addressed by the conventional handshaking/coordination mechanism between two homogeneous networks employing the same radio access technology. In this paper, we present a coexistence protocol, called Spectrum Sharing for Heterogeneous Coexistence (SHARE), that mitigates the hidden terminal problem for the coexistence between two types of networks: one that employs a time-division-multiplexing-based MAC protocol and one that employs a carrier-sense-multiple-access-based MAC protocol. Specifically, SHARE utilizes beacon transmissions and dynamic quiet periods to avoid packet collisions caused by the hidden terminals. Our analytical and simulation results show that SHARE reduces the number of packet collisions and guarantees weighted fairness in partitioning the spectrum among the coexisting secondary networks. <s> BIB004 </s> Survey on coexistence of heterogeneous wireless networks in 2.4 GHz and TV white spaces <s> Introduction <s> Internet of things (IoT) paradigm poses new challenges to the communication technology as numerous heterogeneous objects will need to be connected. To address these issues new radio technologies and network architectures need to be designed to cater to several future devices having connectivity demands. For radio communications, the frequency spectrum allocation will have to be adapted for efficient spectrum utilization considering new bandwidth and application requirements. Novel research directions based on the use of opportunistic radio resource utilization such as those based on cognitive radio (CR) technology will have to be pursued for efficiency as well as reliability. ::: ::: Cognitive Radio is a promising enabler communication technology for IoT. Its opportunistic communication paradigm is suited to communicating objects having event driven nature, that generate bursty traffic. Cognitive Radio can help overcome the problems of collision and excessive contention in the wireless access network that will arise due to the deployment of several objects connected to infrastructure through radio links. However, there are several issues that need to be addressed before cognitive radio technology can be used for Internet of things. ::: ::: This paper surveys novel approaches and discusses research challenges related to the use of cognitive radio technology for Internet of things. In addition, the paper presents a general background on cognitive radio and Internet of Things with some potential applications. Our survey is different from existing surveys in that we focus on recent advances and ongoing research directions in cognitive radio in the context of Machine to Machine and Internet of Things. We review CR solutions that address generic problems of IoT including emerging challenges of autonomicity, scalability, energy efficiency, heterogeneity in terms of user equipment capabilities, complexity and environments, etc. The solutions are supported by our taxonomy of different CR approaches that are classified into two categories, flexible and efficient networking, and tackling heterogeneity. This paper intends to help new researchers entering the domain of CR and IoT by providing a comprehensive survey on recent advances. <s> BIB005 </s> Survey on coexistence of heterogeneous wireless networks in 2.4 GHz and TV white spaces <s> Introduction <s> In traditional wireless sensor networks communicating on a single channel data throughput measured at the sink is constrained by the radio capability, interference, and collisions. Enabling a multi-channel transmission is a potential solution to alleviate the above problem and improve the network performance. Many approaches have been proposed to exploit multiple channels on unlicensed frequencies. The advanced development of cognitive radio enables wireless sensor networks to use vacant licensed channels. Cognitive radio wireless sensor networks enable a dynamic channel selection with the restriction of releasing a channel when a primary user is present. When nodes are set on different channels, coordination has to be carefully designed to ensure a successful transmission. This issue is mainly addressed at the MAC and network layers. In this paper, we provide an intensive survey on various aspects of traditional and cognitive multi-channel wireless sensor networks. Different approaches are categorized based on their underlying topology. Major developments are discussed and drawbacks of the existing approaches are identified. <s> BIB006
The last two decades have witnessed an unprecedented success of wireless networks due to the proliferation of inexpensive, widely available wireless devices, resulting in a significant densification of deployed wireless networks, which have been applied from individual body monitoring to satellites communication. However, given the limited spectrum resources, many of these wireless networks should operate at least partially overlapped or even on the same spectrum band. Such phenomenon, termed as networks coexistence, is pronounced through a lot of spectrum bands, especially in 2.4 GHz industrial, scientific and medical (ISM) band. BIB002 As multiple wireless communication network standards (e.g. Bluetooth, ZigBee and WiFi) are operating on this band for different applications (Internet of Things (IoT), wireless sensor networks (WSNs), individual wireless communication etc.), the wireless networks communication in this band has more complexities than other bands. On the contrary, some authorized spectrum bands are only used in limited geographical areas or periods of time, which lead a lot of spectrum resources wasted. In order to reutilize these vacant spectrum resources, cognitive radio (CR), as a promising technology, has emerged to allow secondary users (SUs) unlicensed networks to access underutilized spectrum bands which is authorized to the primary users (PUs).  BIB001 So that, CR technology has many benefits on wireless networks' data transmission under complex environment by improving spectrum utilization, which gives out numerous novel ideas (e.g. CR for IoT, CR in vehicle networks and CR WSN).  BIB005 BIB006 Due to the ongoing research of CR networks, new CR network standards are required to propose on TV White Spaces (TVWSs) for experiments. Incompatible communication pattern of heterogeneous CR network standards has also caused spectrum competing, and new CR networks coexistence challenges which are different with traditional coexistence scenario have been appeared.  BIB003 Therefore, in order to introduce heterogeneous networks coexistence precisely, the wireless networks coexistence mechanisms of 2.4 GHz and TVWSs would be studied as representatives in this article. Due to the heterogeneous natures of the coexisting networks, the coexistence task is particularly challenging. Specifically, the heterogeneity may contain one or more following aspects: Heterogeneity in wireless technologies at the physical layer: Coexisting networks may employ different wireless technologies, such as IEEE 802.11 (WiFi),  IEEE 802.15.1 (Bluetooth) 12 and IEEE 802.15.4 (ZigBee),  all of which share the same 2.4 GHz ISM band. Due to their different physical (PHY) layers, each two networks of them cannot decode the packets of each other directly. Heterogeneity in medium access mechanisms: Coexisting networks may use different medium access mechanisms, for example, WiFi and some ZigBee networks are based on Carrier Sense Multiple Access (CSMA) mechanism, while the other types of ZigBee networks use Time Division Multiple Access (TDMA)-based medium access pattern. They are by nature conflicting with each other. Heterogeneity in network protocols: Coexisting networks may use different network protocols with different packet formats. As a result, they cannot communicate with each other directly as the packets are not interpretable by others. Heterogeneity in power level: Coexisting networks may transmit their data packets at different power levels, for example, the maximum transmission power of a WiFi node is 20 dBm compared with that of a ZigBee node which is only 0 dBm. The heterogeneity in power level may cause the hidden terminal problem, which, as analysed later in our survey, may significantly degrade the system performance. Heterogeneity in applications and Quality of Services (QoS) requirement: The applications running in coexisting networks may be heterogeneous. A ZigBee network which is utilized for WSN usually has low bitrate application traffic with high stability guarantee, while a WiFi network may support real-time multimedia applications. Consequently, the QoS requirement of these networks are by nature heterogeneous. We now illustrate the above heterogeneity using the examples of the 2.4-GHz ISM band and TVWSs: 2.4 GHz ISM band: The coexistence problem in this spectrum band is mainly between ZigBee and WiFi networks due to their ubiquitous deployments nowadays. The coexistence has a devastated effect on the performance of ZigBee if the traffic of the WiFi network becomes dense. The reason is that the transmission power of ZigBee nodes is order of magnitude lower than that of WiFi nodes, making it difficult for the latter to be informed of the existence of the former. Even in some particular cases where the WiFi nodes are aware of the existence of the ZigBee nodes since they use different wireless technologies and communication protocols, they cannot coordinate between each other to regulate the access to the spectrum. TVWSs: Due to the development of digital television technology, analogue TV broadcast signals are massively transferred to digital pattern. Then, vacant TV spectrum bands are announced to be experimental bandplan 'TV White Spaces' by FCC (Federal Communications Commission) for novel CR networks working.  Examples include IEEE 802.22 wireless regional area networks (WRAN),  IEEE 802.11af (WiFi over TVWSs)  and ECMA 392 (wireless personal area network (WPAN) over TVWSs). 16 The heterogeneity mentioned above is also present in this scenario such as the incompatible medium access control (MAC)/PHY designs of coexisting networks and the heterogeneous QoS requirements. Formally, we use the term heterogeneous networks coexistence to denote the problem of designing distributed coordination and/or resource allocation mechanisms to achieve harmonious and efficient share of the spectrum resources among the coexisting networks. The coexistence mechanisms should Enable communication and information exchange among heterogeneous networks; Ensure efficient and fair resource allocation among networks; in some cases, this means striking a balance between system-level optimality and fairness among each individual network. To tackle the problem of heterogeneous networks coexistence, we identify the following research challenges: Designing coordination and signalling mechanisms: Given the heterogeneity in wireless technologies and communication protocols, the coexisting networks cannot exchange coordination information among them. However, without coordination, it would be too hard to achieve harmonious coexistence among them. Hence, one fundamental step is to design effective coordination and signalling protocols that can enable communication and information exchange among heterogeneous coexisting networks. Solving the hidden terminal problem: The hidden terminal problem in heterogeneous networks is more complex than the original version in CSMA networks. Specifically, we distinguish two scenarios of the problem: -Asymmetrical scenario: Consider two networks 1 and 2. The transmission power of the nodes in network 2 is higher than that of nodes in network 1, as illustrated by Figure  1 (a). Due to such power asymmetry, node 1 in network 2 cannot be aware of the transmissions of the nodes in network 1; thus, data collision cannot be avoided and causing the hidden terminal problem. -Symmetrical scenario: Again, consider two networks 1 and 2. In the symmetrical case, the transmission power of the nodes in network 1 is the same (or comparable) as that of nodes in network 2, as illustrated by Figure  1 (b). Node 1 is transmitter and node 2 is receiver without power emitting in both networks. In this case, the communication of node 2 in network 1 may be interfered since signal emitters in two networks cannot sense each other. Hence, despite the symmetry in transmission power, the hidden terminal problem still exists because the two networks may have different communication protocols and different PHY interfaces, BIB004 making the classic CSMA/CA (Carrier sense multiple access with collision avoidance) mechanism inapplicable in this scenario. Designing efficient resource allocation mechanisms: Another important issue is the design of efficient resource allocation mechanisms, meeting the heterogeneous QoS requirements of the coexisting networks. Ideally, the radio resource should be allocated among the networks proportionally to their QoS requirements. How to achieve such an equilibrium in a distributed way is the key design problem here. Coexisting with PUs: In TVWSs, the impact of PUs should also be taken into consideration when designing coexistence mechanisms and protocols. In this regard, relevant problems include how to identify a primary signal, how to distinguish the primary signal from secondary signals and how to coordinate the access to spectrum holes left by the PUs among the secondary networks. Due to the fundamental importance of the heterogeneous network coexistence problems in the future wireless communication systems and the particular design challenges brought by the heterogeneity analysed previously, we devote this survey to reporting and analysing the recent technical advance and development of coexistence protocols. Aiming at tracing the latest developments in this field, we attempt to deliver a comprehensive coverage on the existing literatures with a proper technical depth to introduce the design idea and philosophy and analyse the pros and cons of each surveyed coexistence solution. We complete the survey by pointing out a number of important and relevant research challenges that have not been addressed in the existing literatures and that deserve further research attention and investigation. The remaining sections are organized as follows. Section 'Overview and taxonomy of existing coexistence solutions' points out the existing main coexistence solutions on 2.4 GHz and TVWSs. And introduces them in different classifications. Section 'Survey on 2.4 GHz coexistence' provides the main coexistence scenarios and research progresses in 2.4 GHz. Section 'Survey on TVWSs coexistence' provides main coexistence scenarios and research progresses in TVWSs. Section 'Conclusion and challenges' concludes the coexistence solutions mentioned in this article with future research directions which have not been addressed.