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ECE 462/562 PROJECT DESCRIPTION Consider an 8-QAM
digital communication
system over an AWGN channel with power spectral density 0( ) , 2W NS f f= ∀ .
The signal constellation diagram is shown below. 101 100 000 001 010 011 110 111 2φ 1φ ( )1 2
a+ ( )1 2 a+ ( )1 2 a− + ( )1 2 a− + a a a− a− Assuming equal probability of occurrence of the
symbols at the transmitter and a correlator receiver, simulate using the Matlab environment for the SNR range [0, 12] dB in
steps of 2 dBs. To obtain reliable results, transmit enough symbols to collect a minimum of 10 symbols errors per SNR value,
around 100,000 symbols or 400,000 bits per simulation run for high SNR cases (fewer symbols
may suffice at low SNR). If you do not observe at least 10 errors per simulation run, increase the number
of transmitted symbols. Use the suggested block diagram as a guide for the simulation implementation.
The uniform random number generator (RNG) is used to generate the sequence of information symbols
corresponding to the 8 possible 3-bit combinations. The information symbols are mapped into the corresponding signal points
( , )i ia b shown in the signal constellation diagram. The two Gaussian RNGs are used to generate uncorrelated,
zero-mean noise components ( , )I Qn n each of which has a variance 2 0Nσ = (because this is a baseband implementation).
Make sure to use two different seeds in the two random number generators to achieve statistical independence
between the two noise sources. To estimate the SER, divide the total number of QAM symbol errors by the total number
of transmitted QAM symbols. Proceed similarly to estimate the BER. Also, obtain a tight bound for the theoretical SER and
compare it with the estimated SER. Uniform RNG Gaussian RNG 8-QAM signal selector Detector Gaussian RNG
Compare Symbol error counter + + 3-bit symbol 3-bit symboli a ib In Qn 1r 2r You are expected to submit
a written report according to the following template: 1. Problem description 2. Assumptions 3. Analysis (if needed)
4. Simulation setup description 5. Simulation results in the form of BER and SER semilog plots versus SNR in dBs.
6. Discussion of results. 7. Appendix with Matlab code so I can replicate your results.