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Stability and Delay Analysis of an Adaptive Channel-Aware Random Access Wireless Network

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Analytical and Stochastic Modelling Techniques and Applications (ASMTA 2017)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 10378))

Abstract

In this work, we consider an asymmetric two-user random access wireless network with interacting nodes, time-varying links and multipacket reception capabilities. The users are equipped with infinite capacity buffers where they store arriving packets that will be transmitted to a destination node. Moreover, each user employs a general transmission control protocol under which, it adapts its transmission probability based both on the state of the other user, and on the channel state information according to a Gilbert-Elliot model. We study a two-dimensional discrete time Markov chain, investigate its stability condition, and show that its steady state performance is expressed in terms of a solution of a Riemann-Hilbert boundary value problem. Moreover, for the symmetrical system, we provide closed form expressions for the average delay at each user node. Numerical results are obtained and show insights in the system performance.

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Notes

  1. 1.

    This model can capture the case where the wireless channel has strong interference by another external network or when the channel is in deep fading. In both cases we can assume that the channel is in the bad state. It is outside of the scope of this version of the paper to consider detailed physical layer considerations.

  2. 2.

    We consider the general case for \(q_{ik}^{*}\), this can handle cases where the node cannot transmit with probability one even if it is transmitting alone. Such a scenario may occur when the nodes are subject to energy limitations. The study of energy harvesting in random access networks has been considered in [5, 20, 29, 30].

  3. 3.

    We assume this mostly for simplicity, however, our work can be extended for the case that the success probability is not zero when the channel is in the bad state.

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Appendices

A Appendix

Regarding the derivation of (2), the queue evolution in (1) implies,

$$\begin{aligned} \begin{array}{l} E(x^{N_{1,n+1}}y^{N_{2,n+1}})=D(x,y)\left( P(N_{1,n}=N_{2,n}=0)\right. \\ \left. +E(x^{N_{1,n}}1_{\{N_{1,n}>0,N_{2,n}=0\}})[1+s_{G}^{(1)}q_{G1}^{*}\tilde{f}_{G,1/\{G,1\}}(\frac{1}{x}-1)]\right. \\ \left. +E(y^{N_{2,n}}1_{\{N_{1,n}=0,N_{2,n}>0\}})[1+s_{G}^{(2)}q_{G2}^{*}\tilde{f}_{G,2/\{G,2\}}(\frac{1}{y}-1)\right. \\ \left. +E(x^{N_{1,n}}y^{N_{2,n}}1_{\{N_{1,n}>0,N_{2,n}>0\}})[s_{G}^{(1)}q_{G1}(s_{G}^{(2)}\bar{q}_{G2}+s_{B}^{(2)}\bar{q}_{B2})\right. \\ \left. \times (1+f_{G,1/\{G,1\}}(\frac{1}{x}-1)) +s_{G}^{(2)}q_{G2}(s_{G}^{(1)}\bar{q}_{G1}+s_{B}^{(1)}\bar{q}_{B1})(1+f_{G,2/\{G,2\}}(\frac{1}{y}-1))]\right. \\ \left. +s_{G}^{(1)}q_{G1}s_{G}^{(2)}q_{G2}(1+f_{G,1/\{G,1;G,2\}}(\frac{1}{x}-1)+f_{G,2/\{G,1;G,2\}}(\frac{1}{y}-1))\right. \\ \left. +s_{G}^{(1)}q_{G1}s_{B}^{(2)}q_{B2}(1+f_{G,1/\{G,1;B,2\}}(\frac{1}{x}-1))+s_{B}^{(1)}q_{B1}s_{G}^{(2)}q_{G2}\right. \\ \left. \times (1+f_{G,2/\{B,1;G,2\}}(\frac{1}{y}-1))+(s_{G}^{(1)}\bar{q}_{G1}+s_{B}^{(1)}\bar{q}_{B1})(s_{G}^{(2)}\bar{q}_{G2}+s_{B}^{(2)}\bar{q}_{B2})\right. \\ \left. +s_{B}^{(1)}q_{B1}s_{B}^{(2)}q_{B2}+s_{B}^{(2)}q_{B2}(s_{G}^{(1)}\bar{q}_{G1}+s_{B}^{(1)}q_{B1})+s_{B}^{(1)}\bar{q}_{B1}(s_{G}^{(2)}\bar{q}_{G2}+s_{B}^{(2)}\bar{q}_{B2})\right) , \end{array} \end{aligned}$$

where \(1_{\{A\}}\) denotes the indicator function of the event A. Note that

$$\begin{aligned} \begin{array}{c} H(x,0)-H(0,0)=\lim _{n\rightarrow \infty }E(x^{N_{1,n}}1_{\{N_{1,n}>0,N_{2,n}=0\}}),\\ H(0,y)-H(0,0)=\lim _{n\rightarrow \infty }E(y^{N_{2,n}}1_{\{N_{1,n}=0,N_{2,n}>0\}}),\\ H(x,y)-H(x,0)-H(0,y)+H(0,0)=\lim _{n\rightarrow \infty }E(x^{N_{1,n}}y^{N_{2,n}}1_{\{N_{1,n}>0,N_{2,n}>0\}}). \end{array} \end{aligned}$$

B Appendix

In the following, we proceed with the study of the location of the intersection points of \(R(x,y)=0\), \(A(x,y)=0\) (resp. B(xy)). These points (if exist) are potential singularities for the functions H(x, 0), H(0, y), and thus, their investigation is crucial regarding the analytic continuation of H(x, 0), H(0, y) outside the unit disk. We only focus on the intersection points of \(R(x,y)=0\), \(A(x,y)=0\).

For and \(R(x,y) = 0\), \(y = Y_{\pm }(x)\), the resultant in y of the two polynomials R(xy) and A(xy) is \(Res_{y}(R,A;x)=x(x-1)s_{G}^{(2)}q_{G2}\widehat{q}_{21}Z(x)\), where

$$\begin{aligned} \begin{array}{rl} Z(x)=&{}-\widehat{\lambda }_{1}(s_{G}^{(2)}q_{G2}\widehat{q}_{21}+(1+\widehat{\lambda }_{1})d_{1,2})x^{2}+x[(\widehat{\lambda }+\widehat{\lambda }_{1}\widehat{\lambda }_{2})d_{1,2}\\ {} &{}+(s_{G}^{(2)}q_{G2}\widehat{q}_{21}+d_{1,2})s_{G}^{(1)}q_{G1}^{*}\tilde{f}_{G1/\{G1\}}]-s_{G}^{(1)}q_{G1}^{*}\tilde{f}_{G1/\{G1\}}d_{1,2}. \end{array} \end{aligned}$$

Note also that \(Z(0)>0\) since \(d_{1,2}<0\), and \(Z(1)>0\), due to the stability conditions (see Lemma 1). If \(q_{G1}^{*}\le min\{1,\frac{s_{G}^{(2)}q_{G2}\widehat{q}_{21}+(1+\widehat{\lambda }_{2})s_{G}^{(1)}q_{G1}\widehat{q}_{12}}{(1+\widehat{\lambda }_{2})s_{G}^{(1)}\tilde{f}_{G1/\{G1\}}}\}\), then \(\lim _{x\rightarrow \infty }Z(x)=-\infty \), and \(Z(x)=0\) has two roots of opposite sign, say \(x_{*}<0<1<x^{*}\). If \(\frac{s_{G}^{(2)}q_{G2}\widehat{q}_{21}+(1+\widehat{\lambda }_{2})s_{G}^{(1)}q_{G1}\widehat{q}_{12}}{(1+\widehat{\lambda }_{2})s_{G}^{(1)}\tilde{f}_{G1/\{G1\}}}<\alpha _{1}^{*}\le 1\), then \(\lim _{x\rightarrow \infty }Z(x)=+\infty \), and \(Z(x)=0\) has two positive roots, say \(1<\tilde{x}_{*}<x_{3}<x_{4}<\tilde{x}^{*}\) (due to the stability conditions). In the former case we have to check if \(x^{*}\in S_{x}\), while in the latter case if \(\tilde{x}_{*}\in S_{x}\). These zeros, if they lie in \(S_{x}\) such that \(|Y_{0}(x)|\le 1\), are poles of A(xy). Denote from hereon \(\bar{x}=x^{*}\), if \(\alpha _{1}^{*}\le min\{1,\frac{s_{G}^{(2)}q_{G2}\widehat{q}_{21}+(1+\widehat{\lambda }_{2})s_{G}^{(1)}q_{G1}\widehat{q}_{12}}{(1+\widehat{\lambda }_{2})s_{G}^{(1)}\tilde{f}_{G1/\{G1\}}}\}\), and \(\bar{x}=\tilde{x}_{*}\), if \(\frac{s_{G}^{(2)}q_{G2}\widehat{q}_{21}+(1+\widehat{\lambda }_{2})s_{G}^{(1)}q_{G1}\widehat{q}_{12}}{(1+\widehat{\lambda }_{2})s_{G}^{(1)}\tilde{f}_{G1/\{G1\}}}<\alpha _{1}^{*}\le 1\).

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Dimitriou, I., Pappas, N. (2017). Stability and Delay Analysis of an Adaptive Channel-Aware Random Access Wireless Network. In: Thomas, N., Forshaw, M. (eds) Analytical and Stochastic Modelling Techniques and Applications. ASMTA 2017. Lecture Notes in Computer Science(), vol 10378. Springer, Cham. https://doi.org/10.1007/978-3-319-61428-1_5

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