Cross-Layer Modeling of Randomly Spread CDMA Using Stochastic Network Calculus

Code-division multiple-access (CDMA) has the potential to support traffic sources with a wide range of quality of service (QoS) requirements. The traffic carrying capacity of CDMA channels under QoS constraints (such as delay guarantee) is, however, less well-understood. In this work, we propose a method based on stochastic network calculus and large system analysis to quantify the maximum traffic that can be carried by a multiuser CDMA network under the QoS constraints. At the physical layer, we have linear minimum-mean square error receivers and adaptive modulation and coding, while the channel service process is modeled by using a finite-state Markov chain. We study the impact of delay requirements, violation probability and the user load on the traffic carrying capacity under different signal strengths. A key insight provided by the numerical results is as to how much one has to back-off from capacity under the different delay requirements.

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

[2]  Rodney A. Kennedy,et al.  Finite-State Markov Modeling of Fading Channels , 2022 .

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

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

[5]  Jeffrey G. Andrews,et al.  Rethinking information theory for mobile ad hoc networks , 2007, IEEE Communications Magazine.

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

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

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

[9]  Jia Tang,et al.  Cross-layer modeling for quality of service guarantees over wireless links , 2007, IEEE Transactions on Wireless Communications.

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

[11]  Bernard Fino,et al.  Multiuser detection: , 1999, Ann. des Télécommunications.

[12]  Edwin K. P. Chong,et al.  Output MAI distributions of linear MMSE multiuser receivers in DS-CDMA systems , 2001, IEEE Trans. Inf. Theory.

[13]  F. Richard Yu,et al.  Effective bandwidth of multimedia traffic in packet wireless CDMA networks with LMMSE receivers: a cross-layer perspective , 2006, IEEE Transactions on Wireless Communications.

[14]  David Tse,et al.  Linear Multiuser Receivers: Effective Interference, Effective Bandwidth and User Capacity , 1999, IEEE Trans. Inf. Theory.

[15]  Giuseppe Caire,et al.  Coded modulation in the block-fading channel: coding theorems and code construction , 2006, IEEE Transactions on Information Theory.

[16]  Georgios B. Giannakis,et al.  Cross-Layer combining of adaptive Modulation and coding with truncated ARQ over wireless links , 2004, IEEE Transactions on Wireless Communications.

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

[18]  Rüdiger L. Urbanke,et al.  Modern Coding Theory , 2008 .

[19]  Shlomo Shamai,et al.  The impact of frequency-flat fading on the spectral efficiency of CDMA , 2001, IEEE Trans. Inf. Theory.

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