A Network Calculus Approach for the Analysis of Multi-Hop Fading Channels

A fundamental problem in the delay and backlog analysis across multi-hop paths in wireless networks is how to account for the random properties of the wireless channel. Since the usual statistical models for radio signals in a propagation environment do not lend themselves easily to a description of the available service rate on a wireless link, the performance analysis of wireless networks has resorted to higher-layer abstractions, e.g., using Markov chain models. In this work, we propose a network calculus that can incorporate common statistical models of fading channels and obtain statistical bounds on delay and backlog across multiple nodes. We conduct the analysis in a transfer domain, which we refer to as the `SNR domain', where the service process at a link is characterized by the instantaneous signal-to-noise ratio at the receiver. We discover that, in the transfer domain, the network model is governed by a dioid algebra, which we refer to as (min,x)-algebra. Using this algebra we derive the desired delay and backlog bounds. An application of the analysis is demonstrated for a simple multi-hop network with Rayleigh fading channels and for a network with cross traffic.

[1]  Giacomo Verticale A closed-form expression for queuing delay in Rayleigh fading channels using stochastic network calculus , 2009, Q2SWinet '09.

[2]  Mazen O. Hasna,et al.  Outage probability of multihop transmission over Nakagami fading channels , 2003, IEEE Communications Letters.

[3]  Kashif Mahmood,et al.  Cross-Layer Modeling of Randomly Spread CDMA Using Stochastic Network Calculus , 2011, ArXiv.

[4]  Theodoros A. Tsiftsis Performance of wireless multihop communications systems with cooperative diversity over fading channels , 2008, Int. J. Commun. Syst..

[5]  E. O. Elliott Estimates of error rates for codes on burst-noise channels , 1963 .

[6]  W. Wang,et al.  Quality-of-service performance bounds in wireless multi-hop relaying networks , 2011, IET Commun..

[7]  Ahmed Ali Mohammed,et al.  Integral transforms and their applications , 2009 .

[8]  Frank Kelly,et al.  Notes on effective bandwidths , 1994 .

[9]  Ibrahim Matta,et al.  Markov-based channel characterization for tractable performance analysis in wireless packet networks , 2004, IEEE Transactions on Wireless Communications.

[10]  Giacomo Verticale,et al.  An Analytical Expression for Service Curves of Fading Channels , 2009, GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference.

[11]  Jean-Yves Le Boudec,et al.  Network Calculus: A Theory of Deterministic Queuing Systems for the Internet , 2001 .

[12]  San-qi Li,et al.  A wireless channel capacity model for quality of service , 2007, IEEE Transactions on Wireless Communications.

[13]  Ness B. Shroff,et al.  A central-limit-theorem-based approach for analyzing queue behavior in high-speed networks , 1998, TNET.

[14]  Almut Burchard,et al.  A Min-Plus Calculus for End-to-End Statistical Service Guarantees , 2006, IEEE Transactions on Information Theory.

[15]  Fumio Ishizaki,et al.  Queuing Delay Analysis for Packet Schedulers With/Without Multiuser Diversity Over a Fading Channel , 2007, IEEE Transactions on Vehicular Technology.

[16]  Dapeng Wu,et al.  Effective capacity-based quality of service measures for wireless networks , 2004, First International Conference on Broadband Networks.

[17]  Kashif Mahmood,et al.  On the Flow-Level Delay of a Spatial Multiplexing MIMO Wireless Channel , 2011, 2011 IEEE International Conference on Communications (ICC).

[18]  John G. Proakis,et al.  Digital Communications , 1983 .

[19]  Alhussein A. Abouzeid,et al.  Queuing network models for delay analysis of multihop wireless ad hoc networks , 2006, IWCMC '06.

[20]  Markus Fidler,et al.  WLC15-2: A Network Calculus Approach to Probabilistic Quality of Service Analysis of Fading Channels , 2006, IEEE Globecom 2006.

[21]  Masoud Ardakani,et al.  Asymptotically-Exact Performance Bounds of AF Multi-Hop Relaying over Nakagami Fading , 2011, IEEE Transactions on Communications.

[22]  Yong Liu,et al.  Stochastic Network Calculus , 2008 .

[23]  A.-T. Nguyen,et al.  A Tandem Queue Model for Performance Analysis in Multihop Wireless Networks , 2007, 2007 IEEE Wireless Communications and Networking Conference.

[24]  Ekram Hossain,et al.  Tandem Queue Models with Applications to QoS Routing in Multihop Wireless Networks , 2008, IEEE Transactions on Mobile Computing.

[25]  Dapeng Wu,et al.  Effective capacity: a wireless link model for support of quality of service , 2003, IEEE Trans. Wirel. Commun..

[26]  Yuming Jiang,et al.  Analysis of Stochastic Service Guarantees in Communication Networks: A Server Model , 2005, IWQoS.

[27]  Florin Ciucu,et al.  Non-asymptotic throughput and delay distributions in multi-hop wireless networks , 2010, 2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

[28]  Cheng-Shang Chang,et al.  A time varying filtering theory for constrained traffic regulation and dynamic service guarantees , 1999, IEEE INFOCOM '99. Conference on Computer Communications. Proceedings. Eighteenth Annual Joint Conference of the IEEE Computer and Communications Societies. The Future is Now (Cat. No.99CH36320).

[29]  Pingyi Fan,et al.  Effective capacity of a correlated Rayleigh fading channel , 2011, Wirel. Commun. Mob. Comput..

[30]  Paolo Giacomazzi,et al.  Bounded-Variance Network Calculus: Computation of Tight Approximations of End-to-End Delay , 2008, 2008 IEEE International Conference on Communications.

[31]  Chengzhi Li,et al.  A Network Calculus With Effective Bandwidth , 2007, IEEE/ACM Transactions on Networking.

[32]  Yang Yang,et al.  A Cross-Layer Analytical Model of End-to-End Delay Performance for Wireless Multi-Hop Environments , 2010, 2010 IEEE Global Telecommunications Conference GLOBECOM 2010.

[33]  L. B. Milstein,et al.  On the accuracy of a first-order Markov model for data transmission on fading channels , 1995, Proceedings of ICUPC '95 - 4th IEEE International Conference on Universal Personal Communications.

[34]  Pingyi Fan,et al.  Effective capacity of a correlated Nakagami-m fading channel , 2012, Wirel. Commun. Mob. Comput..

[35]  Jun Cai,et al.  A Weighted Queue-Based Model for Correlated Rayleigh and Rician Fading Channels , 2011, IEEE Transactions on Communications.

[36]  E. Gilbert Capacity of a burst-noise channel , 1960 .

[37]  P. Sadeghi,et al.  Finite-state Markov modeling of fading channels - a survey of principles and applications , 2008, IEEE Signal Processing Magazine.

[38]  Fady Alajaji,et al.  A Binary Communication Channel With Memory Based on a Finite Queue , 2007, IEEE Transactions on Information Theory.

[39]  Markus Fidler,et al.  An End-to-End Probabilistic Network Calculus with Moment Generating Functions , 2005, 200614th IEEE International Workshop on Quality of Service.

[40]  Hong Shen Wang,et al.  Finite-state Markov channel-a useful model for radio communication channels , 1995 .

[41]  Cheng-Shang Chang,et al.  Performance guarantees in communication networks , 2000, Eur. Trans. Telecommun..