MSc Communications and Signal Processing with Extended Research

Fees for entry in 2027 have not yet been set. For reference, the fees for the academic year beginning September 2026 were as follows:

• MSc (full-time)
  UK students (per annum): £14,700 year 1, £7,350 year 2
  International, including EU, students (per annum): £38,400 year 1, £19,200 year 2

The fees quoted above are fully inclusive of tuition, administration and computational costs.

Fees for entry are subject to yearly review. The University reserves the right to increase your tuition fee by up to 7% each year for courses lasting more than one year, including to reflect rising costs associated with delivering our educational and wider student experience. Postgraduate fees information .

Always contact the admissions team if you are unsure which fee applies to your qualification award and method of attendance.

International student CAS deposit

Self-funded international applicants are required to pay a deposit of £2500 towards their tuition fees before a confirmation of acceptance for studies (CAS) is issued. Some applicants will be required to pay a higher deposit. More information on tuition fee deposits .

All students should normally be able to complete their programme of study without incurring additional study costs over and above the tuition fee for that programme. Any unavoidable additional compulsory costs totalling more than 1% of the annual home undergraduate fee per annum, regardless of whether the programme in question is undergraduate or postgraduate taught, will be made clear to you at the point of application. Further information can be found in the University's Policy on additional costs incurred by students on undergraduate and postgraduate taught programmes (PDF document, 91KB).

We offer a number of postgraduate taught scholarships and awards to outstanding UK and international students each year.

The University of Manchester is committed to widening participation in master's study, and allocates £300,000 in funding each year. Our Manchester Master's Bursaries are aimed at widening access to master's courses by removing barriers to postgraduate education for students from underrepresented groups.

We also welcome the best and brightest international students each year and reward excellence with a number of merit-based scholarships. See our range of master’s scholarships for international students .

And, if you have completed an undergraduate degree at The University of Manchester, or are currently in your final year of an undergraduate degree with us, you may be eligible for a discount of 10% on tuition fees if you choose to study on a taught postgraduate course here. Find out if you're eligible and how to apply .

For more information on master's tuition fees and studying costs, visit the University of Manchester funding for master's courses website to help you plan your finances.

Brief Description Of The Unit:

Introduction to DSP and linear systems.

Convolution and correlation. Using impulse function to represent discrete signals; description of convolution using linear superposition; Fourier interpretation of convolution; simple filtering using convolution; auto-correlation and cross-correlation; cross-correlation, matched filters and signal-to-noise ratio enhancement; temporal smearing and pseudo random bit sequences.

Fourier analysis. The continuous trigonometric Fourier series for periodic signals; data representation and graphing; the continuous trigonometric Fourier series for aperiodic signals; observations on the continuous Fourier series; exponential representation of the Fourier series; the continuous Fourier transform; discrete Fourier analysis; introduction to the fast Fourier transform.

Discrete Fourier properties and processing. Window functions; spectral leakage; representation of spectral data; considerations of phase; key properties of the discrete Fourier transform; discrete Fourier transform signal processing.

The Laplace transform. Its use in differential equation; the s-plane; circuit analysis; analogue filter design.

The z-transform and digital filter design. Definitions and properties; digital filters, diagrams and the z transfer function; filter deign using pole-zero placement; FIR and IIR filters: merits and disadvantages.

Signal sampling. The process of sampling; signal digitisation; principles of analogue to digital and digital to analogue conversion; ADCs and DACs in system.

Design of FIR filters. The window method; phase linearity; the frequency sampling method; software for arbitrary FIR design; inverse filtering and signal reconstruction.

Design of IIR filters. The bilinear z-transform; the BZT and 2nd order passive systems; digital Butterworth and Chebyshev IIR filters; pole-zero placement revisited; biquad algorithm design strategies; FIR expression of IIR responses.

Adaptive filters. Brief theory of adaptive FIR filters; the least mean square (LMS) adaptive FIR algorithm; use of the adaptive filter in system modelling; delayed (single) input adaptive LMS filters for noise removal; the true (dual input) adaptive LMS filter.

Real time DSP: the ADSPBF706 design. System architecture; assembly code programming; real time system design; peripheral interfacing; FIR, IIR and adaptive filters in real time.

DSP in audio applications: reverberation, equalization and string synthesis.

Basic toolbox operations: linear scaling / gain control; addition (mixing); averaging; white noise; PBRS generators; real-time implementation; sine wave and function generation; function approximation.

Quadrature and multi-rate signal processing: the Hilbert transform; waveform modulation; waveform detection/demodulation; envelope detection and rectification; quadrature frequency translation; decimation; interpolation; base-band sampling; IF and under sampling, frequency shift and recovery.

Audio and musical affects: Spectrogram analysis; musical note synthesis – plucked strings; reverberation, echo, vibrato, chorus, flanging; equalization.

The course unit aims to:

• Provide a thorough and complete introduction to the subject of modern digital signal processing.
• Emphasise the links between the theoretical foundations of the subject and the essentially practical nature of its realisation.
• Encourage and understanding through the use of algorithms and real world examples.
• Provide useful skills through detailed practical laboratories, which explore both off-line and real-time DSP software and hardware.

On successful completion of the course, a student will be able to:

ILO 1: Demonstrate an advanced mastery and detailed knowledge of the founding principles of DSP, and understand how the various fundamental equations 
both operate and are constructed.

ILO 2: Recognise the different classes of problem in digital signal processing, and to decide upon appropriate methodologies in their solution. Identify time-domain 
and spectrum-based approaches.

ILO 3: Code, with expertise, and test off-line and real-time DSP algorithms, both using PCs and dedicated DSP hardware. 

ILO 4: Design, from system level, a complete DSP engineering solution (hardware and software specification) intended for real-time use

ILO 5: Develop real-time software using an Eclipse-based coding and debugging framework.

ILO 6: Understand and develop DSP solutions in a range of widely encountered problem spaces, including audio, communications and advanced signal recovery.

Lectures; laboratories; interactive PDF notes that include fully developed software, clickable audio notes and audio examples.

Laboratory in real-time DSP. This comprises six programming tasks (team based) and one design report (individual). 

Digital Signal Processing: A Practical Approach, Emmanuel C. Ifeachor and B Jervis

Foundations of Digital Signal Processing: Theory, algorithms and hardware design, 
Patrick Gaydecki