MULTIPLE FEEDBACK SUCCESSIVE INTERFERENCE CANCELLATION FOR

MU-MIMO USING IDD RECEIVER

By: Supervisor:

M.Sangeetha Ms.M.Kanthimathi,M.Tech,PhD

( 41910403015 ) Asst Professor / Gr- II

AGENDA:

Objective

Introduction About Turbo multiuser detectorsTypes of Turbo detectors.Principle of decoding

IDD (Iterative Detection and Decoding)Receiver Interference Cancellation MAP Decoder Simulation Results References

To obtain improved BER performance and reduced complexity for coded systems by implementing Iterative Detection and Decoding Receiver (IDD) with the proposed MB-MF-SIC detector.

OBJECTIVE:

INTRODUCTION:

Multiuser Detection:

1. Refers to detection of data from multiple users when observed in a non-orthogonal multiplex.

2.Detection problem normally occurs in CDMA systems(Non-orthogonal)

Turbo Multiuser Detection: 1.Refers to joint channel decoding and multiuser

detection using an iterative exchange of soft info between two processes.

TURBO MULTIUSER DETECTORS:

Optimum MUD( Matched Filter) Linear MUD (MMSE Detector ) Non Linear MUD (Decision Feedback MUD)

OPTIMUM MUD:

Matched filter:

1. Requires knowledge of the amplitude of all “k” users

after transmission through the channel. 2.complexity issue.

LINEAR MUD:

Minimum Mean Square Error Detector:

1.Linear constraint can restrict the performance.

2.Easy to exist adapting algorithms.

NON LINEAR DETECTOR:

Decision Feedback MUD:

1.Feedback is used to reduce the MAI(Multiple Access Interference)

2.can’t applied to realistic wireless channel since it requires accurate channel estimates.

IDD (ITERATIVE DETECTION AND

DECODING ) RECEIVER: Recent type Based on turbo-principle. Decoding is an iterative process. Use previously made decisions to reduce MAI. Soft decisions are passed back and forth b/w two SISO

channel decoders with interleaving. Interference cancellation is of 2 types.

a) Parallel Interference Cancellation

b) Successive Interference Cancellation

INTERFERENCE CANCELLATION:

PARALLEL IC

• Simultaneously process all the K users.

• Cancel their interference after decoding independently.

• Requires more than one iteration per user. Cos 1st iteration generates noisy estimates for all the K users.

• Subsequent iterations becoming increasingly more accurate

SUCCESSIVE IC

• Requires atleast K iterations• Each iteration is much less

complex than in PIC, being performed for only one user.

PRINCIPLE OF IDD:

SISO DETECTOR:

A posteriori log likelihood ratio (LLR) of the -th convolutionally 𝑗encoded bit of the -th user’s channel coding block is given by𝑘

MAP DECODER:

SIMULATION RESULTS:

INFERENCE:

NO OF

ITERATIONS

BER VALUES OBTAINED

Conventional SIC MF-SIC MB-MF-SIC

1 0.04135 0.0309 0.02133

2 0.02283 0.01286 0.0003131

3 0.02192 0.01051 0.0008497

4 0.02118 0.01051 0.0003922

[1]. Peng Li, Rodrigo C. de Lamare, and Rui Fa,

‘‘Multiple Feedback Successive Interference Cancellation Detection for Multiuser MIMO Systems, ” IEEE transactions on wireless communications, vol. 10, no. 8, august.2011.

[2].C. Windpassinger, L. Lampe, R. F. H. Fischer, and

T, Hehn, “A performance study of MIMO detectors,” IEEE Trans. Wireless Commun., vol. 5, no. 8, pp. 2004– 2008, Aug. 2006.

[3].R. Fa and R. C. de Lamare, “Multi-branch successive interference cancellation for MIMO spatial multiplexing systems,” IET Commun., vol. 5, no. 4, pp. 484–494, Mar. 2011.

REFERENCES:

[4]. M. Chiani, “Introducing erasures in decision-feedback equalization to reduce error propagation,” IEEE Trans. Commun., vol. 45, no. 7, pp. 757–760, July 1997.

[5]. X. Wang and H. V. Poor, “Iterative (Turbo) soft interference cancellation and decoding for coded CDMA,” IEEE Trans. Commun., vol. 47, no. 7, pp. 1046–1061, 1999

[6]. A. Paulraj, R. Nabar, D. Gore, Introduction to Space-Time Wireless Communications. Cambridge University Press, 2003.

THANK YOU