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ES96T

MSc Assignment 2023

ADVANCED WIRELESS SYSTEMS AND NETWORKS MODULE

Assignment Weighting and typical hours work: 40% of the module, 60 hours.

Learning outcomes assessed:

●   Understand and implement 3GPP channel models for cellular networks.

●   Model the downlink (DL) of a basic 4th generation (4G) cellular network using MATLAB/Python software.

●   Implement optimal radio resource management (RRM) in orthogonal frequency division multiple access (OFDMA) system.

Context/Introduction/Background to the assignment:  Based on Lectures 9-14 (4G cellular network) of the module along with further research required for some questions.

Formatting requirements: Electronic reports along with relevant MATLAB/Python scripts must be submitted.

Submission date/deadline: Monday, Week 32, 12 noon (8 May). Submission via Tabula.

Assessment  criteria/mark  scheme:  Marking is out of 100% and the marks allocated to each question are shown at the end of each question.  80% of marks attributed to technical quality of answers. 20% of marks attributed to presentation.

YOU WILL GET 0 MARKS IF YOU SUBMIT A PUBLICLY AVAILABLE CODE FROM WEBSITES DIRECTLY.

Additional Useful Resources: You will be able to download the pathloss infor- mation and the relevant research papers from the student resources in Moodle.

Feedback format:  Each submitted report will be marked electronically and an electronic copy of the feedback will be provided for each report.

1.      (a)    A cellular communication system follows the Cost-231” pathloss model (line-of-sight case).  The carrier wave frequency is 1 GHz and the base station transmits at 1 W. What is the pathloss in dB scale at a distance of 1000 m from the base station? (5 marks)

(b)    Assume that the standard deviation of shadow fading is given by σ =

4 dB. If the minimum acceptable signal level for coverage is given by -108.6 dB, compute the coverage probability, Pc , and outage probability (i.e., the user not being in coverage) Pout  at a distance of 1000 m from the base station? (10 marks) (Total 15 Marks)

2.    Construct a square cell of dimension 1 km × 1 km. Assume that a base station is placed at the center of each cell.  Then place a single user terminal per cell whose location is chosen according to a uniform random distribution within the cell.

The BS has a maximum transmit power of 5 W and the noise power is -104 dBm.  Consider the Okumara-Hata channel model (given in lecture notes and also in student resources). The carrier frequency is given by 800 MHz, the base- station height is 50 m and the mobile station height is 2 m. The channel model must also account for slow fading (shadowing).  The gain due to antenna pat- terns can be ignored. Assume that the cell divides the total available bandwidth into 4 subchannels. The shadowing gain of each subchannel is independent and identically distributed.

(a)    The BS uses adaptive modulation and coding (AMC). Write a MATLAB

script to perform optimal power allocation over the channels under AMC. You must use the algorithm provided in reference [1]. (30 marks)

(b)    Vary the BS transmit power between 0.5 W to 5 W in steps of 0.5 W. Plot

the resulting sum rate under waterfilling and optimal power allocation.  (5 marks) (Total 35 Marks) 

3.    In a setting similar to Question 2, now consider a 2 km  × 2 km square 2- dimensional simulation space.  Divide the simulation space into 4 square cells of dimension 1 km × 1 km. Assume that a base station is placed at the center of each cell. Then place a single user terminal per cell whose location is chosen according to a uniform random distribution within the cell.

Assume that the BS maximum transmit power, noise power, and the channel model identical to Question 2.

(a)    Write a MATLAB/Python script to implement the iterative multi-user

waterfilling algorithm to nd the per BS optimal subchannel power allo- cation that maximizes the sum rate of the all UTs in the system.  The code must take the system parameters as inputs.  You must follow the algorithm proposed in [2]. (40 marks)

(b)    In a plot, show the convergence of the transmit power for the UTs over

the iterations of the algorithm implemented in Question 2(a). (10 marks)   (Total 50 Marks)

References

[1] W. Guo, S. Wang, and X. Chu, “Capacity expression and power allocation for ar- bitrary modulation and coding rates,” in Proc. IEEE Wireless Communications and Networking Conference (WCNC), 2013, pp. 3294–3299.

[2] W. Yu, “Multiuser water-filling in the presence of crosstalk,” in Proc. Informa-

tion Theory and Applications  Workshop, Jan 2007, pp. 414–420.