Simulation of DPCM and ADM Systems Christopher Mansour Department of Computer and Communications Engineering American University of Science and Technology, AUST Beirut, Lebanon christopher.mansour@hotmail.com Roger Achkar Department of Computer and Communications Engineering American University of Science and Technology, AUST Beirut, Lebanon rachkar@aust.edu.lb Gaby Abou Haidar Department of Computer and Communications Engineering American University of Science and Technology, AUST Beirut, Lebanon gabouhaidar@aust.edu.lb Abstract— Through years, Digital Communication systems, Pulse Coded Modulation (PCM), Linear Delta Modulation (LDM), Differential Pulse Coded Modulation (DPCM), and Adaptive Delta Modulation (ADM), have proven their unlimited advantages over analog communication systems, in term of error minimization, and distances of transmission enhancement. However two of these systems, the Pulse Coded Modulation and Linear Delta Modulation, still have some weaknesses limiting their advantages; these limitations negatively affect the communication process causing quantization error, slope overload distortion and granular noise. On the other hand, communication engineers have developed two additional digital communication systems which are the Adaptive Delta Modulation (ADM) and the Differential Pulse Coded Modulation (DPCM) in order to solve the aforementioned problems. This paper discusses the implementation and simulation of the aforementioned digital communication systems using Simulink (The Math Works, Inc., Natick, MA, USA) showing the effect of different types of noise when applied to the channel, thus, proving the importance of DPCM and ADM systems in eliminating such effects and ensuring a successful transfer of data. Keywords- Adaptive Delta Modulation, Differential Pulse Coded Modulation, Pulse Coded Modulation, Linear Delta Modulation. I. INTRODUCTION Digital communications is the transfer of data over a point-to-point or even point-to-multipoint communication channel, examples of which are copper wires, optical fibers, and wireless communications media. The data is represented as an electromagnetic signal, such as an electrical voltage, radio-waves, or micro waves [1]. While analog communications is the transfer of continuously varying information signal, digital communications is the transfer of discrete messages. The messages are either represented by means of line codes, or by limited set of continuously varying form using the digital modulation methods [2]. Common techniques exist for the digital modulation process in order to make the process of transmitting data feasible, such as the PCM and the LDM. However, these two techniques have problems such as the quantization error resulting from PCM, granular noise and slope overload distortion resulting from LDM. To observe the previously mentioned problems, and their solution, the digital modulation systems are implemented and simulated using Simulink. The relevance of this work lies in its ability to determine, by simulation, the effect of noise on the transmission channel of the data, and prove how two of these systems, the Differential Pulse Coded Modulation and the Adaptive Delta Modulation, work and eliminate the aforementioned problems. II. BACKGROUND INFORMATION A. Pulse Coded Modulation (PCM) Pulse Coded Modulation (PCM) is a method used to digitally represent sampled analog signals; in PCM a signal is represented by a sequence of coded pulses. A PCM stream is a digital representation of an analog signal where the magnitude of the analog signal is sampled regularly at uniform intervals, with each sample being quantized to the nearest value within a range of digital steps [3]. PCM has been used in digital telephone systems and is also the standard form for digital audio in computers and compact disks. However, PCM is not typically used for video in consumer applications such as DVD and DVR because it requires two high bit rate [3]. The performance of a PCM system is influenced by two major sources of noise, namely the channel noise which is introduced anywhere between the transmitter and the receiver; and the quantization noise which is introduced in the transmitter and is carried all the way to the receiver output. This noise is signal dependent in the sense that it disappears when the message signal is switched off [4]. The basic operations performed by the PCM transmitter are: sampling in which the signal is sampled with a train of narrow rectangular pulses and changed into a discrete time signal; quantizing in which the discrete values are approximated and changed into levels and this would be a new representation of the signal which is discrete in time and amplitude, and, encoding in which the obtained levels are changed to bits. As for the PCM receiver, it consists of the regenerative repeater for timing, equalization and