Recognition Method of Signals of DVB-S2 and DVB-S2X Standards on the Basis of Effective PLHEADER Field Decoding

Abstract

The number of electronic devices is constantly increasing. This results in strict requirements for noise protection and sensitivity of new communication devices. Currently, there is a wide range of methods used to implement communication devices with a high level of noise protection based on algorithms for efficient demodulation and decoding. One of the main parts of the process of receiving a digital signal is to determine which signal is coming to the input of the receiver. This process is reduced to scanning frequencies and detecting signal parameters and is an important component of digital radio communication systems. Signal detection provides further correct processing and interpretation of the received information. The article considers the signals transmitted according to the DVB-S2 standard and its extended DVB-S2X revision. Both versions of the standard have almost the same structure at the physical layer. The similarity of the physical layer signals leads, for example, to the fact that if the frequency setting is incorrect, the DVB-S2 receiver can receive a signal of the DVB-S2X standard. In this case, it is not possible to ensure proper processing of the transmitted information. The development of an effective method for detecting the revision and decoding of service information of the physical layer of the DVB-S2/S2X standard solves this problem and expands the possibilities of designing new digital electronics and communication systems with high noise resistance. This paper presents a detector that allows you to determine to which revision the transmitted signal belongs and to determine the parameters of the frame. The detector consists of frame synchronization system, the demodulator and the PLSCODE field decoder. The formulas for calculating the bits of the PLSCODE field and decoding the service information for the DVB-S2 and DVB-S2X broadband notification standards, respectively, are proposed. The software model of the described method is developed. Experimental calculations of the ROC curve and the miss detection probability of the signal-to-noise ratio were performed. The obtained simulation results show the effectiveness of the proposed detection method even at negative signal-to-noise ratios.