# Image Transmission over Cognitive Radio Networks for Smart Grid Applications
## 1 Introduction  
Nowadays, the concept of Smart Grid (SG) networks as the next generation of electricity networks covers various aspects of technical, economical and social affairs. In these networks, a two-way path is considered for both Energy and Data flows [1; 2; 3; 4]. These two flows are not only independent but also have mutual functional effects [5]. Smart grids utilize modern communication networks [6; 7; 8; 9], cyber security measures [4], computational intelligence and efficient information systems throughout the energy production supply chain including distributed generation (DG) resources [10], transmission lines, substations, distribution lines, and end-users as an integrated complex system [11; 12]. This description covers a full range of energy systems from the production point to the endpoints at the customer section. Its purpose is to provide a clean, safe, reliable, flexible, and stable system. In these wide networks, interoperability of various production technologies,information and communication technologies with each other and adapting them to traditional infrastructures of power network leads to the complexity of smart grids [12; 13; 14]. With the development of smart grids, many new applications are also developing [5]. One of the most important issues in the development of smart grids is communication networks which should transmit a wide range of information. There are many different communication technologies for the infrastructure of smart grids [1; 15; 16; 17]. Considering the fact that smart grid is a very wide and complex system of systems with high industrial standards, designing of communication networks must be done in such a way that improves quality of service (QoS), tolerance capability and reliability [18]. The smart grid communication technologies cover various types of networks with different areas and applications which should be fitted with relevant requirements [12; 19]. Some network types are mentioned below [20]:  
1. Wide area networks (WANs) which connect large geographic areas. Phase Measurement Units (PMU) [21; 22; 23], and Wide Area Monitoring Systems (WAMS) [24] are some examples of these networks. WAMS is the only reference that provides information about the angles of current and voltage of the network simultaneously and precisely throughout the entire network [9]. 2. Field Area Networks (FANs) or Neighbor Area Networks (NANs) [25; 26] which provide infrastructures for communication among Intelligent Electrical Devices (IEDs) together and their connections with circuit breakers, actuators, and transformers for automation of DGs, substations and monitoring lines in Advanced Distribution Automation (ADA) applications of SGs. 3. Home Area Networks (HAN) which includes customers' networks and other application networks in customer domain for home automation, smart homes, smart meters, and etc. [20; 27]. Figure 1 demonstrates various network types in SGs. Wide ranges of network types with various data mean that these infrastructures should carry a massive amount of information such as control signals, measured data, monitoring data, multimedia end etc. via communication networks. In addition to the challenging issue of high volume data  
Figure 1: Communication networks and their interconnections within smart grids [28]. transmission, the end-to-end delay is an extremely important problem for SGs, especially for power protection systems. For example, in circuit breakers, any latency in the control command signals can lead to destructive impacts on the power network. Therefore, IEEE and IEC, as two main standard organizations for power systems, had defined solid standards for delays in the SGs including the IEEE 1646 [29] and IEC 61850 [28]. Some details about these standards are collected in Tables 1 and 2. Now, there are increasing demands of multimedia applications in SG communication networks that inherently require a huge amount of bandwidth and well-designed resource allocations methods.