DATE: June 14, 2007 TO: Pierre Collinet FROM: Chinmoy Gavini SUBJECT: A proposal for quantifying tradeoffs in the Physical Layer’s modulation methods of the IEEE 802.15.4 protocol through simulation INTRODUCTION The objective of this proposal is to discuss the problem statement of quantifying modulation tradeoffs in the IEEE 802.15.4 protocol through MATLAB simulation. The Physical Layer (PHY) of any telecommunications protocol is an abstraction of the bits that carry information from a source to a destination. Modulation methods are techniques for encoding digital information in the form of bits onto analog media such as electronic cable or air. The scope of the project is baseband simulation of the modulation, demodulation, and wireless channel using MATLAB’s Signal Processing and Communication Toolbox. The IEEE 802.15.4 protocol is a Wireless Personal Area Network (WPAN) protocol that accommodates lower power requirements, and therefore lower data rates compared to other wireless protocols. One can apply the protocol in areas such as consumer electronics, home security, personal healthcare, automotive sensing, and industrial process control [1]. Other potential applications include systems in which communication is not the dominant feature [1]. An example of such a system is a pressure sensor in a manufacturing plant. Although most sensors in a manufacturing plant communicate continuously with the central controller, some sensors only communicate with the controller for five minutes each week. Therefore, a low power requirement prolongs the sensor’s battery life, and a low data rate is acceptable. Current adopters of the IEEE 802.15.4 PHY include the HART Communication Foundation [2]. My qualifications for completing the project consist of the Telecommunications courses that I have taken and my practical experience working at the HART Communication Foundation. I have taken classes in Communication Theory, Real-Time DSP, Telecommunication Networks, and Data Structures. In this proposal, I discuss the simulation and analysis of the IEEE 802.15.4 protocol using MATLAB’s Signal Processing and Communication Toolbox. I will complete the project in six weeks by July 26th. There are no project expenses at this time.2 PROBLEM DEFINITION The purpose of the project is to quantify tradeoffs in the modulation methods of the IEEE 802.15.4 protocol through simulation. I propose to simulate the baseband processing of the IEEE 802.15.4 PHY layer in MATLAB with Offset-Quadrature Phase Shift Keying (O-QPSK) modulation for the 2.4 GHz PHY and Binary Phase Shift Keying (BPSK) modulation for the 868 and 915 MHz PHY. All three PHY layers use Direct Sequence Spread Spectrum (DSSS). MATLAB’s Signal Processing and Communications Toolbox is directly applicable to this project. The simulations’ channel model is the UltraWideBand (UWB) model, which the IEEE 802.15.4a channel modeling subgroup has recommended. Other potential candidates for a channel model are the Rayleigh fading and Rician fading models. After the simulation is complete, I will quantify the tradeoffs by plotting Bit Error Rate (BER) of each modulation method, comparing data throughput of each modulation, comparing data throughput versus implementation complexity, and verifying the simulation results against the following table [3]: Table 1. Expected characteristics of IEEE 802.15.4 [3] Band Frequency Band Bit Rate Symbol Rate Modulation Chip Rate 868 MHz 868-868.6 MHz 20 kb/s 20 ksymbols/s BPSK 300 kchips/s 916 MHz 902-928 MHz 40 kb/s 40 ksymbols/s BPSK 600 kchips/s 2.4 GHz 2.4 – 2.4835 GHz 250 kb/s 62.5 ksymbols/s O-QPSK 2 Mchips/s Implementation complexity refers to memory and processor requirements. I will use additional modulation comparison methods if they are appropriate for the project. According to Dr. Brian Evans, an appropriate channel model for this project has to include “time-varying gain for fading”, “time-varying finite impulse response filter for multipath effects”, and Additive White Gaussian Noise (AWGN) [4]. The UltraWideBand (UWB) channel model proposed by the IEEE 802.15.4a channel modeling subgroup meets these constraints. The3 UWB model has a nd−pathloss law, frequency dependent pathloss, a modified Saleh-Valenzuela model, block fading, and Nakagami distribution for small-scale fading [5]. I will add Additive White Gaussian Noise (AWGN) to the channel modeling subgroup’s model. For background information on the Saleh-Valenzuela channel model, modulation, and Direct Sequence Spread Spectrum (DSSS), please refer to Appendix A. PROBLEM ANALYSIS AND APPROACH My preliminary approach to the problem statement consists of evaluating the merits of some channel models, researching additional modulation comparison methods, and dividing the simulation into the ideal case and the realistic case. The ideal case consists of the modulation, demodulation, DSSS and AWGN without the channel model. I will add the channel model once the modulator, demodulator, and PN generator work correctly in the ideal case. A design solution to the problem consists of first decomposing the telecommunication system into three modules: the transmitter, receiver, and channel. The transmitter consists of the Bits to Symbols converter, PN Multiplier, and Modulator. The modulator is either an O-QPSK modulator or a BPSK modulator. The receiver consists of the O-QPSK or BPSK Demodulator, PN Multiplier, and Symbols to Bits converter. The channel consists of the signal distortion due to the channel model and AWGN. Please refer to Figure 1 below. Figure 1: Simulation Block Diagram Bits to Symbols PN Multiplier BPSK/O-QPSK Modulator BPSK/O-QPSK Demodulator PN Multiplier Symbols to Bits Channel model effects Noise(AWGN)4 The project activity consists of writing the MATLAB code without channel effects, adding the channel effects, and quantifying the performance using BER plots and other comparison methods. I will test the simulation in each stage. I will unit test each module and perform integrated tests on the entire simulation as I add code. Comparing the modulation methods is a significant part of the design. One can compute the theoretical Bit Error Rate using MATLAB’s BERTool. This theoretical plot would serve as a standard against which the actual Bit Error Rate would be compared. To generate the actual Bit Error Rate plot for the BPSK and O-QPSK modulation, I will create a MATLAB function