cks of 95, 103, 118, 134, 148, 159, 204, and 244 bits to output blocks of 160 reconstructed speech samples. The coding scheme for the multi-rate coding modes is the so-called Algebraic Code Excited Linear Prediction Coder (ACELP). At each 160 speech samples, the speech signal is analyzed to extract the parameters of the CELP model (LP filter coefficients, adaptive and fixed codebooks' indices and gains). These parameters are encoded and transmitted. At the decoder, these parameters are decoded and speech is synthesized by filtering the reconstructed excitation signal through the LP synthesis filter. The AMR codec uses a VAD method to recognize the active periods, and the data are only transferred within this period. For 12.2 kbps coding rate, each 20ms voice frame is 244 bits (12.2kbps * 20ms). During the inactive period, the data volume is rapidly reduced, and only a Silence Insertion Descriptor (SID) packet is sent at the beginning of the inactive period, an AMR SID frame has only 36 bits. Packet Size SID Packet Active period 244 bits Inactive period 36 bits Figure A.5: AMR Speech Codec Model for 12.2 kbps speech traffic Appendix A.7 Self-Similarity There are a number of different, not equivalent, definitions of self-similarity. This definition tightly follows reference [KLL03]. Consider a weakly stationary discrete time stochastic process X = (X1,X2,X3,...) with constant mean, finite variance and autocorrelation function r(k). Further, let X(m) denote a new time series obtained by averaging X over non over- lapping blocks of size m. That is, for k = 1,2,3... the time series X (m) 1=(1/m)(Xkm-m+1++Xkm)and = let p(m) denote the autocorrelation function of X( m) . The process X is called strictly self-similar with self-similarity (or Hurst) parameter H if mX (m) has the same finite dimensional distributions as mH X for all m>1. The above is the mathematical definition of self-similarity. The physical meaning of self-similarity is that the traffic rates, i.e. number of packets or bytes per time unit, has the burst