Smart grid requires reliable and timely delivered sensed data to meet the expectation of various SG applications in satisfactory service delivery. The traditional or conventional SG used probable WSN for monitoring and control in delivering the sensed data. This WSN makes used of static resource allocation to statically allocate resources to the sensor
node and communication devices. To this end, the CRSN paradigm makes used of dynamic resource allocation due to the presence of dynamic spectrum access (DSA) capability. This CRSN paradigm thrives well to dynamically allocates radio resources to sensor nodes and communication devices in a SG ecosystem. Hence, CRSN makes used of dynamic resource allocation schemes to allocate resources optimally among multiple resource com- petitive sensor nodes. As seen from the preceding section, the dynamic resource allocation schemes improve energy efficiency in the communication devices, for example, it helps to extend the battery power life of sensor nodes. Unfortunately, the energy efficiency schemes in terms radio resource allocation are lacking in CRSN based SG.
Also, looking at Table 3.2, schemes for adaptive modulation and throughput maximization are lacking in CRSN based SG. In addition, schemes that covers multiple resource optimiza- tion criteria. To this end, the authors believe that designing a holistic cross layer scheme that accommodates energy efficiency, throughput maximization and adaptive modulation while leveraging optimization criteria such as interference avoidance, hand-offs reduction, fairness, priority, and QoS support will go a long way in yielding optimal results in CRSN based SG monitoring and control.
Many SG applications such as distribution automation, demand response, SCADA, surveil- lance and multimedia applications including security of automatic metering infrastructure (AMI) are research critical. Hence, a robust and reliable communication that can withstand harsh environmental SG condition are required to meet the demand of these research critical application. Based in this, attention should be drawn to the direction of design and optimization of a cross layer framework for seamless exchange of signaling and control information across the protocol layers of the sensor node and communication device for CRSN based SG.
It is pertinent therefore to also note that research is highly needed in the development of unified solution schemes that accommodate three or overall of resource optimization criteria for CRSN based SG. Specifically, research should be directed towards energy ef- ficient adaptive modulation, energy efficient throughput maximization, energy efficient spectrum access, and hand-offs reduction. In fact, the energy efficiency issue is an open research direction in CRSN based SG domain. A hybrid energy harvesting that utilized radio frequency alongside other mechanisms for harvesting energy perpetually for the power constraints sensor node remains an open research subject in the domain of SG generally.
3.5
Chapter Summary
In this chapter, CRSN based SG as a new paradigm for modern SG which is totally different from the traditional power grid and also different from the conventional grid is introduced. The existing power grid uses static resource allocation technique to allocate resources to sensor nodes and communication devices in the SG network. Radio resource allocation that leverage DSA capability to dynamically allocate radio resources to the sensor nodes and communication devices in CRSN based SG environment is explored. The overview, unique characteristics, functionalities, and challenges of CRSN in SG are discussed. Also, a proposed DHC architecture is presented in this chapter. Radio resource optimization criteria which is an important consideration for resource allocation in CRSN based SG has been highlighted. The various resource allocation schemes, i.e., RRA architecture in a CRSN based SG, have been presented in this chapter. Performance analysis of RRA based on throughput improvement criteria in CRSN for SG is also reported in this chapter. Suggestions are made in order to improve communication device connectivity and seamless communication among multiple resource competitive sensor node in the CRSN based SG ecosystem. Future research direction which include design and optimization of cross layer framework for radio resource allocation in CRSN SG has been highlighted.
Finally, energy efficiency and hybrid energy harvesting schemes for perpetual power supply to the battery power constraints sensor node are also pointed out as an open research area in CRSN SG.
Performance Analysis of
Correlated Multi-Channels in
CRSNs based Smart Grid
4.1
Introduction
Dual/multi antenna channels of the sensor nodes including too close spacing of sensor nodes deployment in a SG environment can lead to the problem of dual/multi correla- tion fading channels. This correlation can lead to degradation of the signals as well as co-channels interference. In addition, there exist also problem of spectrum inefficiencies, the signal-interference-noise-ratio (SINR), multipath fading, and shadowing peculiar to SG harsh environmental condition including interference from SG equipment which also pose great challenges to CRSN based SG. Hence, performance analysis of the correlated multi- channels will help in the improvements of SG communications. Reliable communication systems are keys to achieving the benefits of Smart Grid (SG) [160].
However, spectrum inefficiencies and interferences including the aforementioned prob- lems are challenges to reliable communication in SG. Consequently, cognitive radio is the preferred solution to the problem of spectrum inefficiencies. Cognitive Radio has the capability of Dynamic Spectrum Access (DSA) to access spectrum opportunistically, hence is the preferred promising option to solve the problem of spectrum inefficiencies. Therefore, integration of CRSNs which is a combination of Cognitive Radios and Wireless Sensor Networks (WSNs) in SG will help to address the spectrum problem. A network of CRSN devices can exploit these licensed bands opportunistically through opportunistic spectrum access (OSA) as secondary users (SUs), whereas the licensed users (legitimate users), or the primary users (PUs), have precedence over the spectrum band.
paradigm in SG [162]-[168], such as link reliability, co-channel interference, bandwidth, and latency [11], [9], [169]-[170]. In addition, irregular channel conditions and electromag- netic signal-to-noise-ratio-interference from the SG equipment caused by harsh environ- mental conditions of the SG adversely affects the overall network performance [171]. Hence, one of the non-optimal ways to attain a better throughput-received -signal of the sensed data at the sensor nodes is by deploying sensor nodes with multi channels in close ranges. Nevertheless, there exist a multi co-channels in CRSN paradigm due to the closeness of sensor nodes with multi channels deployed in CRSN based SG environment. These result to dual/multi correlated channels including co-channel interference which adversely affects the received signal of the communication network performance. Thus, leading to high sym- bol error probability (SEP) or high bit error rate (BER) with poor signal to noise ratio (SNR). Also, other factors such as multipath fading and shadowing do impair the received signal network performances. Consequently, the problems of correlation of signals can typically be addressed by introducing algorithmic transformation approach and reception diversity technique; such that, a performance analysis will be carried out in order to obtain an improved average signal-to-noise-ratio (SNR) by combining two or more desired signal of the multiple channels. This performance improvement by maximization of the average SNR will give rise to interference mitigation and optimal throughput of transfer of the sensed data in the SG network. Before performance improvement is delved into, a look at the approach of related works in literature is necessary.
The rest of this chapter is organized with the following subsections as follows: related works; moment generating function (MGF) based performance analysis of error probability of dual/multi correlated channels in CRSN based SG including the use of algorithmic ap- proach and transformation technique for converting correlated channels into non-identical and independent signal under Nakagami-q distribution; simulation results and chapter summary.