CALL FOR PAPERS
             IEEE Journal on Selected Areas in Communications 

              NONLINEAR OPTIMIZATION OF COMMUNICATION SYSTEMS

   Linear  programming  and  other classical optimization techniques have
   found  important  applications  in  communication  systems for several
   decades.  Recently, there has been a surge in research activities that
   utilize  the power of recent developments in nonlinear optimization to
   tackle  a  much  wider  scope  of  work  in the analysis and design of
   communication  systems,  touching every "layer" of the layered network
   architecture,  and  resulting  in  intellectual  and practical impacts
   significantly  beyond  the  established frameworks in the early 1990s.
   These  research activities are driven by both new demands in the areas
   of   communications  and  networking,  and  new  tools  emerging  from
   optimization  theory.  Such tools include new developments of powerful
   theories  and  highly efficient computational algorithms for nonlinear
   convex optimization, as well as global solution methods and relaxation
   techniques for nonconvex optimization.

   The  phrase  "nonlinear optimization of communication systems" carries
   at least three different meanings. In the most straightforward way, an
   analysis or design problem in a communication system may be formulated
   as  either  minimizing  a cost or maximizing a utility function over a
   set  of  variables  confined within a constraint set. In a more subtle
   and  recent approach, a given network protocol may be interpreted as a
   distributed   algorithm   solving  an  implicit,  global  optimization
   problem.  In  yet another approach, the underlying theory of a network
   control  method  or  a communication strategy may be generalized using
   nonlinear   optimization  techniques,  thus  extending  the  scope  of
   applicability  of  the  theory. Over the last few years, the nonlinear
   optimization  framework  has been successfully applied to a wide range
   of communication sytems, from the high speed Internet core to wireless
   networks,  from  coding and equalization to broadband access, and from
   information theory to network topology models.

   We  are  soliciting  papers  on  the topics of the applications of the
   theories   and   algorithms   of  nonlinear  optimization  (convex  or
   nonconvex)  and  Lagrange  duality to various aspects of communication
   systems  analysis  and  design,  including  parallel  and  distributed
   optimization techniques for problems where the problem data or control
   mechanisms are spatially distributed.
     * Networking protocols as distributed optimization algorithms:
          + Internet protocols such as TCP/AQM/IP
          + Wireless network protocols such as medium access and routing
          + Allocation  of  network resources such as bandwidth, rate, or
            power
          + Queuing systems performance optimization
          + Optimization-based models of network traffic and topology
     * Digital  communications signal processing algorithms via nonlinear
       optimization methods:
          + Signal processing algorithms such as equalization, precoding,
            modulation, shaping, and channel estimation
          + Wireless transceiver design
          + Wireless MIMO systems design
          + Power allocation and spectrum management in DSL
          + Multiuser detection algorithms
     * Information-theoretic limits obtained by nonlinear optimization:
          + Characterization and computation of channel capacity and rate
            distortion
          + Multi-terminal channel capacity and data compression problems
          + Information rates in channels with memory
          + Channel and source code optimization
          + Generalization and application of waterfilling algorithms
     * Cross-layer design through nonlinear optimization decomposition:
          + TCP/IP, TCP/MAC, TCP/PHY interactions
          + Scheduling based on wireless fading environment
          + Other  cross-layer  problems formulated through the framework
            of nonlinear optimization
          + Topics  that  involve  more than one of the three main topics
            above:  networking,  physical  layer  signal  processing, and
            information theory, in the nonlinear optimization frameworks

   Prospective  authors  should  follow  the IEEE J-SAC manuscript format
   described   in   the   Information  for  Authors.  Only  original  and
   unpublished  papers  will  be  considered.  Authors  are encouraged to
   include  adequate mathematical background materials in their papers to
   make the results and methodologies accessible to a wide range of J-SAC
   readers.

   All papers should be submitted in PDF format via email to Mung Chiang,
   chiangm@princeton.edu, according to the following timetable:

                 Manuscript Submission:   September 1, 2005
                 Acceptance Notification: February 15, 2006
                 Final Manuscript Due:    April 15, 2006
                 Publication:             3rd Quarter 2006

   Guest Editors:
     * Mung  Chiang,  Electrical  Engineering Dept, Princeton University,
       USA, chiangm@princeton.edu
     * Steven  Low,  Computer  Science  &  Electrical  Engineering  Dept,
       California Institute of Technology, USA, slow@caltech.edu
     * Tom   Zhi-Quan   Luo,  Electrical  &  Computer  Engineering  Dept,
       University of Minnesota, USA, luozq@ece.umn.edu
     * Ness  Shroff,  Electrical  &  Computer  Engineering  Dept,  Purdue
       University, USA, shroff@ecn.purdue.edu
     * Wei  Yu,  Electrical  &  Computer  Engineering Dept, University of
       Toronoto, Canada, weiyu@comm.utoronto.ca