# Image Transmission over Cognitive Radio Networks for Smart Grid Applications
## 2 Related Works
In [57], the use of wireless sensor network for electrical power systems along with opportunities and challenges had been investigated and a practical evaluation was presented in different environments of the electrical power system. They concluded that with the help of wireless sensor networks, it is possible to identify outages in the power network and manage it before any hierarchical damage on the network. In fact, the real-time recognition of network faults based on WSNs can play a significant role in outage reduction and optimization of related parameters such as System Average Interruption Frequency Index (SAIFI) and System Average Interruption Duration Index (SAIDI). Other research works in the use of wireless sensor networks are available in [54; 55; 58]. In [54], the implementation of an intelligent monitoring system on more than one wireless sensor network, with particular emphasis on constructing a secure routing infrastructure using routing protocol for low loss power networks was presented. In [56], a closed-loop energy management scheme with a WSN was introduced, which can be used as the network infrastructure of an industrial energy management system. Its importance lies in its high security, intelligence, and low cost hardware. In [53], three wireless sensor networks named HART, Zigbee, and ISA100.11a were evaluated. All these networks are based on IEEE 802.15.4 standard protocol and available as low-cost industrial options for smart grids. But their applications are limited to low bitrate applications so they are not well fitted to delay-sensitive and high volume data transmission in multimedia applications. Generally, using traditional WSNs in SGs suffers from some restrictions which are listed below:  
* Using overcrowded ISM bands with high delay due to high competition in channel access [59; 60]. * High retransmission rate because of high interference in ISM bands [61; 45]. * Low energy efficiency due to high retransmission [62; 63; 64]. * These networks were essentially developed for low data rate applications with low efficiency for multimedia transmission [52]. * Low spectrum efficiency [65; 66]. In contrast to classical sensor networks, it is possible to benefit from cognitive radio networks (CRNs). Cognitive radio (CR) is a very important wireless technology for achieving spectrum efficiency. In CRNs, two networks are defined, the first one named primary networks and the second one called secondary networks. The licensed bound are dedicated to Primary Users (PUs) but Secondary Users (SUs) also can use them with lower priority providing that they are Idle [62; 65; 67]. Opportunistic usage of unoccupied licensed bands in CRNS can increase the spectral efficiency noticeably. Due to the availability of the licensed band and the possibility of transmission based on multichannel methods, interference will be reduced in large-scale cognitive radio networks [68]. As a result, CRNs are increasingly being developed in both infrastructure-based networks and Ad Hoc/Sensor Networks in recent years [67]. Ref. [69] had studied the performance of the innovative hierarchical modulation based multimedia streaming in CR communication systems with this assumption that imperfect channel sensing on transmission power level and also interference were accessible. In this research, the efficient power control method that can minimize weighted sum of average bit error rates (BERs) of high priority (HP) bits and low priority (LP) bits or its upper bound subject to peak/average transmit power and average interference power constraints was introduced and a low-complexity power control approach was developed. They had achieved closed-form expressions of error probabilities for both HP and LP bits in hierarchical quadrature amplitude modulation (HQAM) over Nakagami-m fading channels under sensing uncertainty. Their focuses were more concentrated on the physical layer (PHY) rather than the MAC layer.