Belief Propagation Methods for Intercell Interference Coordination in Femtocell Networks

Interference coordination is a fundamental challenge in emerging femtocellular deployments. This paper considers a broad class of interference coordination and resource allocation problems for wireless links based on utility maximization with a general linear mixing interference model suitable for complex femtocellular systems. The resulting optimization problems are typically hard to solve optimally even using centralized algorithms but are an essential computational step in implementing rate-fair and queue stabilizing scheduling policies in wireless networks. We consider a belief propagation framework to solve such problems approximately. In particular, we construct approximations to the belief propagation iterations to obtain computationally simple and distributed algorithms with low communication overhead. Notably, our methods are very general and apply to, semi-static and dynamic interference coordination problems including the optimization of transmit powers, transmit beamforming vectors, fractional frequency reuse (FFR) and sub-band allocations to maximize the above objective. Numerical results for femtocell deployments demonstrate that such algorithms compute a very good operating point in typically just a couple of iterations.

[1]  Jian Ni,et al.  Improved bounds on the throughput efficiency of greedy maximal scheduling in wireless networks , 2011, TNET.

[2]  Sundeep Rangan,et al.  Generalized approximate message passing for estimation with random linear mixing , 2010, 2011 IEEE International Symposium on Information Theory Proceedings.

[3]  R. Srikant,et al.  Network Optimization and Control , 2008, Found. Trends Netw..

[4]  Ness B. Shroff,et al.  Joint Congestion Control and Distributed Scheduling for Throughput Guarantees in Wireless Networks , 2007, IEEE INFOCOM 2007 - 26th IEEE International Conference on Computer Communications.

[5]  Amir Dembo,et al.  Large Deviations Techniques and Applications , 1998 .

[6]  Michael I. Jordan,et al.  Graphical Models, Exponential Families, and Variational Inference , 2008, Found. Trends Mach. Learn..

[7]  Erik Dahlman,et al.  3G Evolution: HSPA and LTE for Mobile Broadband , 2007 .

[8]  Jeffrey G. Andrews,et al.  Power control in two-tier femtocell networks , 2008, IEEE Transactions on Wireless Communications.

[9]  András Rácz,et al.  Intercell Interference Coordination in OFDMA Networks and in the 3GPP Long Term Evolution System , 2009, J. Commun..

[10]  M. Bayati,et al.  Max-Product for Maximum Weight Matching: Convergence, Correctness, and LP Duality , 2008, IEEE Transactions on Information Theory.

[11]  Yikang Xiang,et al.  Inter-cell Interference Mitigation through Flexible Resource Reuse in OFDMA based Communication Networks , 2007 .

[12]  Sampath Rangarajan,et al.  Efficient resource management in OFDMA Femto cells , 2009, MobiHoc '09.

[13]  Jian Ni,et al.  Distributed CSMA/CA algorithms for achieving maximum throughput in wireless networks , 2009, 2009 Information Theory and Applications Workshop.

[14]  Tae-Jin Lee,et al.  A New Frequency Partitioning and Allocation of Subcarriers for Fractional Frequency Reuse in Mobile Communication Systems , 2008, IEICE Trans. Commun..

[15]  John Edwards Implementation of network listen modem for WCDMA femtocell , 2008 .

[16]  Ian F. Akyildiz,et al.  The evolution to 4G cellular systems: LTE-Advanced , 2010, Phys. Commun..

[17]  Dmitry M. Malioutov,et al.  Belief Propagation and LP Relaxation for Weighted Matching in General Graphs , 2011, IEEE Transactions on Information Theory.

[18]  Alexander L. Stolyar,et al.  Scheduling algorithms for a mixture of real-time and non-real-time data in HDR , 2001 .

[19]  Andrea Montanari,et al.  The dynamics of message passing on dense graphs, with applications to compressed sensing , 2010, ISIT.

[20]  Jeffrey G. Andrews,et al.  Femtocell networks: a survey , 2008, IEEE Communications Magazine.

[21]  Judea Pearl,et al.  Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.

[22]  Halim Yanikomeroglu,et al.  Interference Avoidance with Dynamic Inter-Cell Coordination for Downlink LTE System , 2009, 2009 IEEE Wireless Communications and Networking Conference.

[23]  Devavrat Shah,et al.  Maximum weight matching via max-product belief propagation , 2005, Proceedings. International Symposium on Information Theory, 2005. ISIT 2005..

[24]  Jie Zhang,et al.  OFDMA femtocells: A roadmap on interference avoidance , 2009, IEEE Communications Magazine.

[25]  Sungwon Lee An Enhanced IEEE 1588 Time Synchronization Algorithm for Asymmetric Communication Link using Block Burst Transmission , 2008, IEEE Communications Letters.

[26]  Ismail Güvenç,et al.  Femtocell Networks , 2010, EURASIP J. Wirel. Commun. Netw..

[27]  Leandros Tassiulas,et al.  Linear complexity algorithms for maximum throughput in radio networks and input queued switches , 1998, Proceedings. IEEE INFOCOM '98, the Conference on Computer Communications. Seventeenth Annual Joint Conference of the IEEE Computer and Communications Societies. Gateway to the 21st Century (Cat. No.98.

[28]  Dongning Guo,et al.  Asymptotic Mean-Square Optimality of Belief Propagation for Sparse Linear Systems , 2006, 2006 IEEE Information Theory Workshop - ITW '06 Chengdu.

[29]  Yeong Min Jang,et al.  Soft QoS-based CAC Scheme for WCDMA Femtocell Networks , 2008, 2008 10th International Conference on Advanced Communication Technology.

[30]  J. Boutros,et al.  Iterative multiuser joint decoding: unified framework and asymptotic analysis , 2001, Proceedings. 2001 IEEE International Symposium on Information Theory (IEEE Cat. No.01CH37252).

[31]  Chirag S. Patel,et al.  System design of CDMA2000 femtocells , 2009, IEEE Communications Magazine.

[32]  Jeffrey G. Andrews,et al.  A Graphical Model Approach to Downlink Cooperative MIMO Systems , 2010, 2010 IEEE Global Telecommunications Conference GLOBECOM 2010.

[33]  Alexander L. Stolyar,et al.  On the Asymptotic Optimality of the Gradient Scheduling Algorithm for Multiuser Throughput Allocation , 2005, Oper. Res..

[34]  Leandros Tassiulas,et al.  Stability properties of constrained queueing systems and scheduling policies for maximum throughput in multihop radio networks , 1990, 29th IEEE Conference on Decision and Control.

[35]  Ness B. Shroff,et al.  Understanding the capacity region of the Greedy maximal scheduling algorithm in multihop wireless networks , 2009, TNET.

[36]  Bruce E. Hajek,et al.  Cooling Schedules for Optimal Annealing , 1988, Math. Oper. Res..

[37]  Sundeep Rangan,et al.  Estimation with random linear mixing, belief propagation and compressed sensing , 2010, 2010 44th Annual Conference on Information Sciences and Systems (CISS).

[38]  Michael L. Honig,et al.  Distributed interference compensation for wireless networks , 2006, IEEE Journal on Selected Areas in Communications.

[39]  Devavrat Shah,et al.  Network adiabatic theorem: an efficient randomized protocol for contention resolution , 2009, SIGMETRICS '09.

[40]  Harish Viswanathan,et al.  Self-Organizing Dynamic Fractional Frequency Reuse for Best-Effort Traffic through Distributed Inter-Cell Coordination , 2009, IEEE INFOCOM 2009.

[41]  J. Walrand,et al.  Sufficient conditions for stability of longest-queue-first scheduling: second-order properties using fluid limits , 2006, Advances in Applied Probability.

[42]  R. Srikant,et al.  Maximizing sum rate and minimizing MSE on multiuser downlink: Optimality, fast algorithms and equivalence via max-min SIR , 2009, ISIT.

[43]  F AkyildizIan,et al.  The evolution to 4G cellular systems , 2010 .

[44]  Jean C. Walrand,et al.  A Distributed CSMA Algorithm for Throughput and Utility Maximization in Wireless Networks , 2010, IEEE/ACM Transactions on Networking.

[45]  Frank Kelly,et al.  Rate control for communication networks: shadow prices, proportional fairness and stability , 1998, J. Oper. Res. Soc..

[46]  Mung Chiang,et al.  Power Control in Wireless Cellular Networks , 2008, Found. Trends Netw..

[47]  R. Srikant,et al.  Low-Complexity Distributed Scheduling Algorithms for Wireless Networks , 2009, IEEE/ACM Transactions on Networking.

[48]  Ashwin Sampath,et al.  Distributed Interference Management and Scheduling in LTE-A Femto Networks , 2010, 2010 IEEE Global Telecommunications Conference GLOBECOM 2010.

[49]  Paolo Giaccone,et al.  Randomized scheduling algorithms for high-aggregate bandwidth switches , 2003, IEEE J. Sel. Areas Commun..