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As the bandwidth for 5G and beyond is very large and the WRFS offers a large number of non-continuous idle spectrum slots in 5G communication as well [ 4 ], there is a requirement to identify the unused spectrum slots not being used by respective licensed users called primary users PUs. Accurate SS allows the secondary users SUs to opportunistically use the vacant spectrum slots as per their wireless applications and vacate when the PU arrives in the network.
This process is termed as spectrum decision. All previously mentioned research contributions are more concept oriented for IoT in 5G network. The RF spectrum accessibility as per the wireless application for the user in IoT environment remains an open research area. Motivated by this, a comprehensive survey on 5G networks embedded with IoT applications based on CR ensuring A6 connectivity by accessing across the entire RF spectrum has been carried out in this chapter.
A case study based on this survey for CR-based IoT in 5G networks has also been proposed to validate the concept. Introduction, related work and the motivation of the work is given in the first section. Evolution to 5G is given in Section 3. IoT in 5G network is described in Section 4. Section 7 concludes the chapter.
Evolution to the fifth generation 5G is the progressive advancement in the telecommunication industry to keep with the growing pace of mobile data traffic, huge volume of device connections and continuous emergence of latest commercial scenarios. Over the last one decade or so, the wireless communications have the capability to connect all the existing mobile technologies, to build a terminal that is to support the voice, video and data applications with respective QoS requirements guaranteed i.
Progressive evolution of Mobile services from 1G to 5G [ 5 ]. This reduces the workload and energy consumption of BS thereby offering a good platform for 5G. The realization of IoT is dependent on internet application scenario based requirements which converge to 5G networks and are not guaranteed in 4G and LTE technologies.
Modern trends and requirements in IoT [ 8 ]. The Internet of Things IoT envisions thousands of constrained devices with sensing, actuating, processing, and communication capabilities able to observe the world with an unprecedented resolution. These connected things will generate huge volume of data that need to be analyzed to gain insight behind this big IoT data. Moreover, in the industrial environments industry 4.
The forthcoming 5G networks are promising not only by increased data rates but also low-latency data communication for latency-critical IoT applications.
While the massive IoT is more concerned about scalability deep coverage and energy efficiency, the later requires ultra-low latency and extreme reliability URLLC. Recently, the fog-to-thing continuum [ 10 ] is proposed to mitigate the heavy burden on the network due to the centralized processing and storing of the massive IoT data.
Fog-enabled IoT architectures ensure closer processing in proximity to the things, which results in small, deterministic latency that enables real time applications and enforced security. The IoT is a modern and the state of the art archetype in the technological advancement which is evolving as a future Internet. As per the principal vision of the IoT, the further requirement is the ubiquity of the Internet, after connecting people anytime and everywhere, is to connect extinct entities.
By providing objects with embedded communication capabilities and a common addressing scheme, a distributed and permeating network of impeccably connected diverse electric and electronic devices is designed, which is to be indigenously cohesive into the existing Internet connections and mobile networks.
Thus allowing for the development of new intelligent services available anytime, anywhere, by anyone and anything. Since the spectrum assignment policy involves expenditures for buying the RF spectrum, the assignment of spectrum for a huge number of devices and objects required for IoT connectivity will result in redundant cost effects.
CRNs due to its typical spectrum utilization characteristic emerge in realization of IoT. Usually, the SU operates in half-duplex mode HD , i. Hence the spectrum sensing should be a continuous process and SU must vacate the licensed channel on arrival of its PU and switch to another suitable channel as per its application, i.
External storage solutions offer nearly unlimited capacity, with dedicated signal processing to sort through data and find signals, interactions or events of interest. This means that the spectrum management holds a great significant in CR technologies and A6 connection. Preserving the required QoS of the users along with their mobility requires spectrum mobility for the SUs in the network, which we now know as 5G network. Because of its mobility, an SU may change its location cell in a cellular network during its transmission and, therefore, will enter a new region in which the targeted RF spectrum slot is already being used by the PU [ 15 ].
The perfect SS techniques provide prior information for which SUs will work [ 5 ]. Since the primary traffic in any cell and region is always time varying and cannot be accurately predicted, therefore, the SUs must have the real time information of RF spectrum slots occupancy status to switch over to the vacant slots for resuming their transmission in case PUs arrive. Similarly, the SS errors are also required to be mitigated. The PUs use their licensed spectrum for their transmissions as per their QoS requirement and the statistical analysis says that this usage remains for a very short period of time.
The decision of accessing the vacant spectrum slots would enable the SU to have A6 connections making an IoT environment. The allocated frequency spectrum for wireless applications is under-utilized due to the emblematic customs of wireless applications [ 16 ]. The conventional approach to spectrum management is very inflexible in the sense that each wireless service provider is assigned an exclusive license to operate in a certain frequency spectrum band.
It has become very difficult to find vacant spectrum bands to either deploy new services or to enhance existing ones [ 17 ]. Spectrum sharing refers to coordinated access to the selected channel by the SUs. Spectrum mobility enables SU to switch over to another channel when a PU is arrived. SS involves identification of spectrum holes and the ability to quickly detect the onset of PU communications in the channels occupied by the SUs.
There are two scenarios as an overlay and underlay for spectrum sharing [ 21 , 22 ]. This scenario is also known as opportunistic spectrum access. This scenario is known as underlay spectrum sharing [ 24 ]. The overlay mode operation is focused in this chapter.
CR systems offer the capability of IoT-Us to improve the spectrum utilization under the existing fixed spectrum assignment policy. ED is the widely used scheme for SS due to its simplicity, easy implementation and it corresponds to the general purpose of SS for heterogeneous wireless communication systems [ 27 ]. MFD requires the exact synchronization and prior knowledge of PU signal, moreover implementation complexity of the sensing unit is large as the SU need receivers for all types of signal [ 29 ].
ED and MFD perform non coherent by calculating the energy of the received signal samples and coherent comparing with the known PU signal detection respectively [ 30 ]. Cyclostationary detection suffers from high complexity as all the cycle frequencies are required to be calculated [ 31 ]. CSS and non-centralized detection have exhibited SS errors due to time lag involved between sensing and its results [ 32 ].
Although the vacant spectrum slots are identified in SS but unless these are not simultaneously occupied through a well-defined decision process, the concept of CR cannot be realized. Therefore, it is imperative to mitigate the SS errors false alarm and miss detection before taking the decision to occupy the sensed vacant spectrum slot. List of SS techniques available in literature [ 33 ]. The performance of CRNs is largely dependent on PU arrival and departure from the spectrum slots, the license of which it holds [ 34 ]. As the RF spectrum band is wide range for various wireless applications, therefore, one PU activity cannot reflect the activity pattern of PU of all wireless applications as these varies from application to application.
As the FCC has approved to use secondary users on licensed RF spectrum only with the condition that PU transmission will not be interfered. This implies that the licensed spectrum will only be occupied when PU is not using it, the underlay occupancy. Moreover, it is very important to ensure that PU is not harmfully interfered. Thus PU activity modeling in wireless communication networks in terms of stochastic geometry is particularly relevant for spectrum decision framework.
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The PU activity, as a simplest case, in CRN can be represented as a print of a stationary random model in a probabilistic way. In particular the locations of the CRNs nodes are seen as the realizations of some point processes. When the underlying random model is ergodic, the probabilistic analysis also provides a way of estimating spatial averages which often capture the key dependencies of the CRN performance characteristics connectivity, stability, capacity, etc. Hence, the PU activity should be modeled with some stochastic arrival and departures probability expression.
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Poisson distribution process PDP provides a near to realistic probability of arrival and departure of the primary user in the network. PDP offers spatio-temporal representation of PU activity model. Moreover, Poisson distribution process is simple and adapts well in wireless communication scenario. This will help in ensuring no interference and will provide basics for mechanism of switching to other available slot, if PU arrives.
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This causes IoT-Us a temporary break in transmission, which is mitigated by simultaneous access in multiple noncontiguous spectrum bands by IoT-Us for their transmission. Even if a PU appears in one of the channels, the rest of the channels will continue to allow SUs to transmit while maintaining their QoS requirements.
In the transmission process of SUs when accessing the channel in a heterogeneous manner, the transmission level measure for PU is given by the PTB as,.
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P i,j is the stationary probability of two dimensional Markov state which is PTB. A survey of spectrum decision in CRNs based on RF spectrum characterization, spectrum selection and CR reconfiguration has been presented in [ 20 ]. Qi che gou zao yu jia shi by Jianguo Zhong Book 2 editions published in in Chinese and held by 2 WorldCat member libraries worldwide.
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