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Evaluating the Bit Error Rate of M-QAM over the AWGN Channel

Evaluating the Bit Error Rate of M-QAM over the AWGN Channel. Abstract. A review on the paper, “Bit Error Probability of M-ary Quadrature Amplitude Modulation”

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Evaluating the Bit Error Rate of M-QAM over the AWGN Channel

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  1. Evaluating the Bit Error Rate of M-QAM over the AWGN Channel

  2. Abstract • A review on the paper, “Bit Error Probability of M-ary Quadrature Amplitude Modulation” • A general expression for the BER of an M-ary square QAM was derived using the advantage of Gray Code Mapping and the assumption of contamination with additive white Gaussian noise.

  3. Error Rates • Usually presented and derived by computation of the symbol error rate or, • by the estimation method of union bounds. • We seldom see expressions for the BER of the modulation schemes.

  4. Reasons behind lack of expressions for the BER • Exact analysis of BER is complicated. • Usually not expressed in closed-form solutions. • Transformation of the symbol error rate to BER is not straightforward.

  5. Reasons why we need BER expressions • Estimation using union bound does not guarantee accuracy and, • at the end of the day, we want to differentiate the efficiencies of the different types of modulation schemes by their very basic unit of representation, bits.

  6. System Model

  7. System Model

  8. BER of 4-QAM

  9. BER of 4-QAM

  10. BER of 4-QAM • We then do the computation of Pb(k), the probability that the kth bit of the in-phase and quadrature phase components are in error in terms of .

  11. BER of 16-QAM

  12. BER of 16-QAM • We start by analyzing the bit assignment (i1q1i2q2) of the constellation points. • We can see that if I,Q < 0, then i1,q1 =1 and if I,Q > 0, then i1,q1 =0 . • With this we could separate the constellation above into 4 regions the same as a 4-QAM constellation. • In this case, an error would occur when the noise is either greater than d or 3d.

  13. BER of 16-QAM

  14. BER of 16-QAM • We now shift our focus to the last two bits (i2q2) of the symbols. • We can see that that the bounds for the decision regions are the lines I, Q = -2d,+2d. • From the regions formed, the bit error cases could now be distinguished. It is easily noted that If I,Q < -2d then i2,q2= 1. If -2d < I,Q < 2d then i2,q2= 0. And If I,Q > 2d then i2,q2= 1.

  15. BER of 16-QAM

  16. BER of 16-QAM

  17. BER of 64-QAM

  18. BER of 64-QAM • In the figure above, each constellation point is represented by a 6-bit symbol composed of three bits each from of the in-phase and the quadrature components, (i1q1i2q2i3q3).

  19. BER of 64-QAM

  20. General BER for Square M-ary QAM

  21. Conclusion • We have just presented a review of the general expression for the BER of an M-ary Gray-coded square QAM over an AWGN channel. • From the computations above, we see that the derivations always take into consideration the fact that square QAM’s are symmetrical and we don’t need to complete the computations. • It is also important to easily distinguish the decision regions specified by the bounds. With the right bounds, the probability of bit error would be determined correctly by the position of the bits and the noise associated to it.

  22. References • [1] J.G. Proakis, Digital Communications, 5th ed. New York: McGaw-Hill, 1995.  • [2] J. Letaief and J. Chuang, “M-PSK and M-QAM BER Computation Using Signal-Space Concepts,” IEEE Trans. Commun., vol.47,pp.181-184, Feb. 1999.  • [3] D. Yoon, K. Cho and J. Lee, “Bit Error Probability of M-aryQuadrature Amplitude Modulation,” Vehicular Tech. Conf. 2000. vol.5, pp.2422-2427, Sept. 2000.

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