MUD: Multi-user detection. Jetmir Palushi Stevens Institute of Technology EE613 DSP for Communications. Overview. MUD in CDMA systems MUD Features Modulation and Implementation Concept Multiple Access Interference (MAI) MUD algorithms Linear Non-Linear Optimal MLSE MUD Detectors
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MUD: Multi-user detection
Stevens Institute of Technology
EE613 DSP for Communications
- Size and weight requirements are not stringent for base station
- Therefore it is currently being implemented for mobile to base station.
- Decorrelating Detector
- Minimum-mean squared error (MMSE)
- Blind (adaptive non-adaptive) techniques
The matrix R is of the form:
- The MMSE detector takes the background noise in to account and utilizes the knowledge of the received signal powers
-It minimizes the mean squared error between the actual data and the soft outputs of the conventional detectors
Advantage: Better error probability performance, and no noise enhancement
Disadvantage: Requires estimation of received amplitudes, and matrix inversion
- The detector doesn’t require the training sequence in order to calculate the channel impulse response
- Requires the knowledge of the signature waveforms and timing information of the desired user
- The limitation is that it works only for short codes
Estimate the interference caused by each
user on the others, re-spread and cancel from
the received signal. This is done through multitude of stages.
- Multistage Detector
- Decision Feedback Detector
- Subtractive Interference cancellation
Successive Interference Cancellation (SIC)
Parallel Interference Cancellation (PIC)
Selective Parallel Interference Cancellation
The concept of the multistage detector is to make a decision in every stage as the name indicates. As shown on the diagram above the received signal is y and the detector produces the decisions x(1) x(2) up to x(n). Where:
The main advantages are:
1) The weakest user will see a tremendous signal gain from the MAI reduction since all of the interfering channel will add up as signals to the weakest user. Hence every user is on a win-win situation.
2) For severe conditions if we remove the strongest user the rest of weaker users will benefit hence the signal can be recovered
3) Can recover from near-far effects
The main disadvantages are:
1) If the strongest estimate is not highly reliable it results on performance degradation
2) As the power profile changes the signals must be reordered
3) Every stage introduces a delay
1) Because of the parallel nature no delays/stage required!
2) Simpler than other linear detectors