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Matlab project help

I am doing my undergratuate course in canada.I am looking for small matlap project related to wireless communication.

Here is the details

BPSK over Flat Fading Channel

Assume BPSK signal X ∈ {−√Es,√Es} are transmitted over the Rayleigh flat fading channels. Consider a

fast fading environment, where the transmitted symbols experience i.i.d. fading and AWGN noise.

Yk = Xkhk + Nk

where hk ∼ CN(0, 1), and Nk ∼ CN(0,No).

Task 2: Simulate Detection Performance over Fading Channels Let SNR = Es/No. For SNR=0:2:14dB,

simulate the ML detector by detecting BPSK symbols. Provide the following curves for bit error rate (BER)

(in log scale) in a single plot

1. The derivation of ML detector for BPSK signaling

2. The analytical BER vs. SNR when the channel is ideal AWGN.

3. The simulated BER of ML detector vs. SNR(dB) for Rayleigh fading channel.

4. The analytical BER vs. SNR(dB) for Rayleigh fading channel.

Discuss what you observe from these plots.

Note: The simulation of actual detector performance at each SNR requires Monte Carlo runs, i.e., each

run has different realizations of the transmitted symbol Xk and noise Nk. Enough Monte Carlo runs will

make your curves smooth. To simulate BER, count all the dtection errors made in all the Monte Carlo runs,

then

P[symbol error] ≈ #of detection errors/#of Monte Carlo runs.

The approximation is better as the # of collected detection errors becomes large. Therefore, we need enough

Monte Carlo runs to collect sufficient number of detection errors to make the simulation result reliable. You

may need more Monte Carlo runs at high SNR and less at low SNR (Lower error probability is expected at

higher SNR. More runs are required to collect the same number of detection errors). For example, you will

need to collect about 50 100 errors to make your result statistically significant. Then if the error probability

is 10��2, you will need 5 × 103 ∼ 104 Monte Carlo runs.

Task 3: Diversity Combining Techniques To improve detection performance over fading channels,

we simulate some diversity combining techniques using multiple received antennas. Consider the multiple

received antenna system. Assume the channel over each Tx-Rx pair is i.i.d. Rayleigh flat fading, and channels

are i.i.d. across Tx-Rx pairs. Again, SNR = Es/No. For SNR = 0:2:14dB, simulate the diversity combining

techniques followed by ML detector for BPSK signaling. Provide the following curves for BER (in log scale)

in a single plot

1. Describe the combining weight for SC, MRC, EGC.

2. The simulated BER vs. SNR(dB) under no diversity (1Rx)

3. The simulated BER vs. SNR(dB) under SC (2Rx, 4Rx)

4. The simulated BER vs. SNR(dB) under MRC (2Rx, 4Rx)

5. The simulated BER vs. SNR(dB) under EGC (2Rx, 4Rx)

Discuss what you observe from these plots.

4 MIMO Communications

Consider now BPSK transmission using a 4 × 4 MIMO system. The channel matrix H is given by

H =

h11 · · · h14

...

...

h41 · · · h44 Matrix

where hij ’s are i.i.d. Rayleigh flat fading channel from Tx j to Rx i. hij ∼ CN(0, 1).

Task 4: Simulate MIMO Beamforming Simulate the BPSK detection performance using MIMO beamforming

technique and ML detector. Let SNR = Es/No, where Es is the total symbol energy transmitted

over all antennas. Describe the MIMO Beamforming algorithm. For SNR = 0:2:14dB, provide the simulated

BER vs. SNR(dB). Compare the performance with those in Task 3, and discuss your observations from

these plots.

Please if u can do it contact with ur details and cost of this project,time requirements

Skills: Electrical Engineering, Electronics, Matlab and Mathematica, Wireless

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