# Analysis and Experimental Validation of Efficient Coded OFDM for an Impulsive Noise Environment
## 1 Introduction  
Intelligence in networks has been a reality for a long time. The novelty is the growing need for flexibility in electrical systems. This need finds a large part of its origin in the development of intermittent energies (wind, solar), which induce rapid variations of production. It is also reinforced by the concern to avoid capacity investments by using the flexibility of demand. To have networks capable of managing this flexibility, it is necessary to introduce new forms of intelligence. This new form of intelligence consists of placing a computer network above the grid to form a Smart Grid (SG). The functions are to ensure better control and optimization of the network and to offer value-added services. This is an evolution that has become possible because it is able to couple computer and electrical technologies in the same equipment and networks at a very low cost. Therefore, for energy companies, the use of this solution becomes unavoidable considering their number of substations and the immense extent of their electrical networks. It is within this framework that sensor networks are deployed in this context of SG since these technologies offer advantages such as a low cost of deployment. Sensor networks will allow remote control of equipment, diagnosis and maintenance of stations through a communication protocol. However, High Voltage (HV) substations are strategic points in the electrical network and are the site of numerous disturbances that can generate noise of the impulse type. This type of noise is well known in the field of electrical engineering and is a source of losses that can degrade the performance of wireless communications [1]. The existingwireless technologies such as ZigBee were not designed for the power grid. They do not consider the different requirements of the industrial environments and cannot guarantee an acceptable quality of communication and good performance [2]. Industrial domains are not taken into account in the design of existing standards because their constraints have particular characteristics (reliability, real-time, multi-path phenomena, low power consumption, safety, etc.). Many previous research works have proposed precise impulsive noise models [3; 4; 5; 6; 7; 8; 9]. For this purpose, in [10], the author suggested a new impulsive noise mitigation technique derived from the application of block-based Compressed Sensing (CS). A semi-analytical error-rate performance was also studied, which demonstrated that the proposed approach is efficient in CS application for impulsive noise detection. Furthermore, Coded-Orthogonal Frequency Division Multiplexing (C-OFDM) systems have been widely used for impulsive noise cancellation. In [11], the authors designed a low-density parity check coded OFDM system applicable to the impulsive noise channel. The results of the proposed approach demonstrated precisely that the performances are much better than the conventional systems. Besides, [PERSON] et al. introduced in [12] an efficient impulsive noise estimation algorithm based on the Alternating Direction Method of Multipliers (ADMM) for OFDM systems using Quadrature Amplitude Modulation (QAM). Simulation results have shown that the proposed method can achieve bit error rate performance improvements at reduced computational complexities compared with the conventional techniques. In our recent work [13], we proposed a resistant physical layer based on the concatenation of Rank metric Code (RC) and Convolutional Code (CC) with OFDM. We have used this model to compare different signalling schemes on this channel [13]. The results showed that our approach is robust and efficient compared to other systems. However, the obtained results are based solely on simulations. Moreover, in the literature, there does not exist experimental results for impulsive noise suppression that can be used as a basis for comparison. Several works have been proposed, but the results are only based on simulations.