TransmitterChannel Receiver Abstract This project involves the analysis and simulation of direct- sequence spread-spectrum (DSSS) communication systems.

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Presentation transcript:

TransmitterChannel Receiver Abstract This project involves the analysis and simulation of direct- sequence spread-spectrum (DSSS) communication systems that employ nonbinary orthogonal modulation using Walsh- Hadamard signals. The goal of the research is to investigate the performance of this type of modulation for communication over channels with additive white Gaussian noise (AWGN) and multipath interference. Using a receiver that utilizes matched- filters, it is found that the bit energy to noise ratio required in order to maintain a certain probability of symbol error increases nonlinearly as the power ratio between direct-path signal power and multipath signal power decreases linearly. Motivations In Personal Communication Service (PCS), the reverse link (mobile station to base station link) uses DSSS technique that employs nonbinary orthogonal modulation using Walsh- Hadamard signals. In another application, high-data-rate wireless local-area networks (WLAN) subject to multipath interference also employ DSSS technique along with nonbinary orthogonal modulation using Walsh-Hadamard signals The System Transmitter: Includes a 64-ary orthogonal modulator followed by an m-sequence generator. Channel: Contains additive white Gaussian noise (AWGN) and multipath interference. Receiver: Includes an m-sequence generator followed by a chip-matched filter followed by 64 parallel discrete-time matched filters and finally followed by a decision device. m-sequence generator Simulation The simulation of the system is done in Matlab, and the properties of the signals, channel, and receiver in the simulation are as follows: Coherent demodulation is employed The chip waveform is a rectangular pulse with amplitude A and duration Tc. The chip-matched filter has a rectangular-shaped impulse response with amplitude B and duration Tc. The multipath delays used are 16 chips and 32 chips. The multipath signal causes intrasymbol interference. The multipath signal attenuation factor, α, is between 0 and 1. The sampling rate of the output of the chip-matched filter is equal to the chip rate. The sampling rate of the output of the 64 parallel discrete-time matched filters is equal to the symbol rate. Results From this graph, it can be observed that as the desired probability of symbol error and power ratio decrease linearly, the increase in the bit energy to noise ratio required to maintain the desired probability of symbol error increases nonlinearly. From this graph, it can be seen that the difference between the multipath degradation for one multipath and two multipaths increases slightly as the power ratio decreases. However, even the largest multipath degradation difference, which occurs when the power ratio is zero, is still small relative to the multipath degradation that occurs for the same power ratio. Therefore, multipath degradation depends primarily on the total power of the multipath component(s) and not on the number of multipath components. Conclusion The system can operate efficiently for any desired probability of symbol error as long as the power ratio is sufficiently high. However, as the desired probability of symbol error decreases, the range of the power ratio, in which multipath degradation becomes significant, increases, which means that the range of the power ratio that provides efficient system operation decreases. References 1. Michael B. Pursley, “Random Processes in Linear Systems.” New Jersey: Prentice Hall, The Math Works Inc., “The Student Edition of Matlab: The Ultimate Computing Environment for Technical Education.” New Jersey: Prentice Hall, Roberto Padovani, “The Application of Spread Spectrum to PCS has Become a Reality: Reverse Link Performance of IS-95 Based Cellular Systems.” IEEE Personal Communications, Third Qrtr, 1994.