Reference no: EM132315475

Advanced Telecommunications Assignment -

Congratulations! Your company recently won a bid to design and implement a multi-carrier wireless communication systems to provide wireless broadband services to a regional city in Queensland. Mobile service providers have overlooked this community due to economic considerations. Deployment of standard communications systems are costly and the Queensland government is looking for a cheaper alternative.

In this task you will perform following tasks to design and test a viable wireless communication system for the above application.

Data collected from an extensive measurement campaign commissioned by Queensland Government can be used to place base station antennas at strategic locations to maximize reliability and coverage. The channel measurement campaign has found that the wireless channel in the intended coverage area shows multi-path characteristics with number of delayed paths with significant delays and a set of measured data is available to estimate the path loss exponent.

You can extract the path loss data and the measured channel delay profile parameters by following the instructions in Part 1. Each group will have a unqie set of data based on their student IDs.

Preliminary Instructions - Download all files to be used in Assignment 2 from blackboard and place them into one working directory. Please also unzip the contents of assignment2.zip into this directory.

There are 2 files contained within assignment2.zip:

1. initialise.m - used to generate the data used in this assignment.

2. A2GenData.p - called by initialise.m

Part 1 - Estimate Path Loss Exponent of the Channel

Large scale fading can be modeled as a combination of the path loss and log normal shadowing. The path loss L_dB in dB as a function of distance d is calculated by

L_dB = L_0,dB + 10n log10(d/d₀) + X_σ,

where L_0,dB is the path loss in dB obtained at the reference distance of d₀ away from the transmitter, n the path loss exponent and X the shadowing component. The shadowing component is Normally distributed when the path loss is specified in dB, and has zero mean with a standard deviation of σ also specified in dB.

In this part you will be estimation of the value of n and σ from data in following two variables.

• d: This vector corresponds to the distance between transmitter and receiver at which a measurement was taken. This units are in meters.
• LdBShadow: This matrix stores the data captured in a measurement campaign. Each row of the matrix corresponds to a new measurement trial. The units are in dB.

1. Present the measured path loss data at different distances in a scatter plot.

2. For each of the distances inside d, calculate the average path loss.

3. Plot the results of the averaged path loss.

4. Use the MATLAB built in function fitlm to find a linear model for the given data.

5. Estimate the path loss exponent.

6. Assuming transmitter and receiver antenna gains are 10dB and 5 dB respectively, receiver sensitivity of -98 dBm, and fade margin of 25 dB estimate the minimum transmitted power required if the receiver is 5 km away from the transmitter.

7. For each of the distance inside d, calculate the standard deviation.

8. Use this information to find an estimate for the standard deviation of X_σ.

Part 2 - Design an OFDM System

You are asked to design a fixed wireless access (FWA) system to provide wireless broadband services to regional Australia. Your system should be capable of offering a 100 Mb/sec download speed using a 40 MHz band centered around 3.6 GHz spectrum. Remember you need to optimise the bandwidth usage and choose the smallest possible modulation scheme to offer good bit-error-rate performance at low transmit power.

1. Load the channel channel.mat file and extract the variables pvec and tvec, where pvec and tvec are channel time delay vector in nanoseconds and the delayed relative power vector of the channel in dB respectively. Plot and label the multipath impulse response of the channel.

2. Estimate the rms delay spread of the channel.

3. Estimate the coherence bandwidth of the channel.

4. If the data requirement of the system is 100 Mbps, design your OFDM system using above information. You need to decide following parameters of your system.

• N - Number of sub-carriers.
• T - OFDM Symbol duration
• Tg - Guard interval
• m - Modulation index (smallest possible.)

Justify your selections.

NOTE: The guard interval T_g > 10 x σ_τ and the Sub-carrier bandwidth Δ(f) ≤ B_c/10, where B_c is the coherence bandwidth of the channel.

5. Estimate the maximum data rate of your system if the maximum allowable modulation index is 8 (256-QAM). Compare the this data rate with that of a equivalent single carrier system.

6. Describe how you can improve the capacity of your system.

7. Write a MATLAB code to simulate the performance of the OFDM system in AWGN channel. Simulate and plot the bit error rate performance within the E_b/N₀ range from 0 dB to 15 dB and compare with the theoretical bit-error rate performance.

You can use built-in MATLAB functions in this step. Some of the useful MATLAB functions would be, fft, ifft, qammod, awgn and biterr.

8. Comment on the observed bit-error-rate performances.

Part 3 - Flat fading Channel

You are able to meet the required data-rate at AWGN channel. Now, you need to simulate the performance of above OFDM system in a Rayleigh fading channel with the impulse response given by pvec and tvec.

h(t) = h δ(t)

where h is a Gaussian random variable with zero mean and σ_h variance. For the following simulation assume σ_h = 1.

Simply adding the two Gaussian Random variables and taking the square root (envelope) gives a single tap Rayleigh distributed process. The phase of such random variable follows uniform distribution. Consider two Gaussian random variables with zero mean and same variance X and Y. Let's define a complex Gaussian random variable as X + i * Y . The envelope follows Rayleigh distribution and the phase will be uniformly distributed. The probability density function (Rayleigh distribution) of the above mentioned amplitude response is given by

f_A(a) = (a/σ²)exp{-(a²/2σ²)}

1. Create two vectors with 10000 samples of a complex Gaussian random variable, h with variance 1 using randn command and find the envelope of and plot its normalised histogram. Compare the normalised histogram against the theoretical Rayleigh distribution.

2. If X_n, (n = 1, 2, . . . , N) is the vector of modulated symbols. The ODFM signal can be generated by, x_k = ifft(X_n), k = 1, 2, . . . N

Assuming fading channel stationery during the OFDM symbol duration, we can find the frequency response of the channel using,

H_n = fft(h) n = 1, . . . N

The FFT output at the receiver can be expressed as

Y_n = H_nX_n + n_n

Therefore, the received signal can be recovered using a single tap equalisation,

X^~_n = Y_n/H_n = X_n + n_n/H_n = X_n + n^~_n

Now, X^~_n can be demodulated to extract the transmitted data. You can assume that full channel information is available at the receiver for the following simulation. In practice, channel needs to be estimated using pilot symbols.

Write a MATLAB code to simulate the performance of OFDM system in flat Rayleigh fading channel within the E_b/N₀ range from 0 dB to 30 dB. Simulate and plot the bit error rate performance and compare with the theoretical bit-error rate performance and the bit-error rate performance in AWGN channel.

3. Comment on the observations.

Part 4 - Performance in a Multipath fading channel

In this section you will simulate the performance of the OFDM system in the measured multipath channel you extracted in Part 1. Let us assume that the power delay profile of the multipath fading channel is given as

h(τ) = p(τ_i)δ(t- τ_i) i = 1 . . . L,
 where L is the number of paths. For the simulation we need to normalise the power. The normalisation factor α can be estimated as

α = 1/(_i∑^Lp(τ_i))

Then the variance of each path can be estimated as,

σ(τ_i) = αp(τ_i)

Finally, the each path can be generated as below,

h(τ_i) = √(σ(τ_i)/2) * (randn(1, K) + 1i * randn(1, K))

where K is the number of channel samples.

1. Update the code written in Part 2 to simulate the performance of OFDM system in multipath Rayleigh fading channel. Simulate and plot the bit error rate performance and compare with the bit-error rate performance in at fading channel.

You can load the channel.mat file to get he multipath delay profile of the channel.

2. Comment on the observations.

Part 5 - Forward Error Control

1. Implement a Forward error correction code to improve the reliability of the received data. You can choose any forward error correction method for this section. You can also use built-in MATLAB functions to implement the chosen error control coding method. Simulate and plot the bit-error rate of the coded OFDM system in the above multipath-fading channel and compare with the bit error rate performance of the un-coded OFDM in multipath-fading channel.

2. Queensland government wants to enhance capability of the proposed wireless systems such that the system can be used for mobile banking and other financial activities. You have been instructed to update the system with an appropriate cyclic-redundancy check code (CRC).

Choose an appropriate CRC code and show how you can implement this in the above system.

3. Estimate the rate at which a user can transmit data when the system is upgraded with the chosen error control coding and CRC scheme.

Reflection (Mandatory)

Each member of the group should write a reflection and appended to the end of your report. Include a short discussion of about 100 words that addresses problems encountered, any lessons learned and things that you would have done differently. This section is mandatory and the assignment is regarded as incomplete if absent. If you had any group concerns throughout the duration of your assignment, please address them here.

Attachment:- Assignment File.rar