Cost Efficient High Capacity Indoor Wireless Access: Denser Wi-Fi or Coordinated Pico-cellular?

Rapidly increasing traffic demand has forced indoor operato rs to deploy more and more Wi-Fi access points (APs). As AP density increases, inter-AP interference rises and may limit the capacity. Alternatively, cellular technologies using centralized i nterference coordination can provide the same capacity with the fewer number of APs at the price of more expensive equipment and installation cost. It is still not obvious at what demand level more sophisticated coordination pays off in terms of total system cost. To make this comparison, we assess the required AP density of three candidate systems for a given average demand: a Wi-Fi network, a conventional pico-cellular network with frequency planning, and an advanced system employing multi-cell joint processing. Numerical results show that dense WiFi is the cheapest solution at a relatively low demand level. However, the AP density grows quickly at a critical demand level regardless of propagation condit ions. Beyond this “Wi-Fi network limit”, the conventional pico-cellular network works and is cheaper than the joint processing in obstructed environments, e.g., furnished offices with walls. In line of sight condition such as stadiums, the joint processing becomes the most viable solution. The drawback is that extremely accurate channel state information at transmitters is needed.

[1]  Shlomo Shamai,et al.  Cooperative Multicell Zero-Forcing Beamforming in Cellular Downlink Channels , 2009, IEEE Transactions on Information Theory.

[2]  David Gesbert,et al.  Adaptation, Coordination, and Distributed Resource Allocation in Interference-Limited Wireless Networks , 2007, Proceedings of the IEEE.

[3]  Rui Chang,et al.  Interference coordination and cancellation for 4G networks , 2009, IEEE Communications Magazine.

[4]  François Baccelli,et al.  A Stochastic Geometry Analysis of Dense IEEE 802.11 Networks , 2007, IEEE INFOCOM 2007 - 26th IEEE International Conference on Computer Communications.

[5]  Wei Yu,et al.  Transmitter Optimization for the Multi-Antenna Downlink With Per-Antenna Power Constraints , 2007, IEEE Transactions on Signal Processing.

[6]  David Tse,et al.  Multicell Downlink Capacity with Coordinated Processing , 2008, EURASIP J. Wirel. Commun. Netw..

[7]  I. Forkel,et al.  A multi-wall-and-floor model for indoor radio propagation , 2001, IEEE VTS 53rd Vehicular Technology Conference, Spring 2001. Proceedings (Cat. No.01CH37202).

[8]  Jeffrey G. Andrews,et al.  Spectrum allocation in tiered cellular networks , 2009, IEEE Transactions on Communications.

[9]  Kareem E. Baddour,et al.  Autoregressive modeling for fading channel simulation , 2005, IEEE Transactions on Wireless Communications.

[10]  Jens Zander,et al.  Is multicell interference coordination worthwhile in indoor wireless broadband systems? , 2012, 2012 IEEE Global Communications Conference (GLOBECOM).

[11]  Anders Furuskar,et al.  Cost Efficient Deployment of Heterogeneous Wireless Access Networks , 2007, 2007 IEEE 65th Vehicular Technology Conference - VTC2007-Spring.

[12]  Jens Zander,et al.  Cost and feasibility analysis of self-deployed cellular network , 2011, 2011 IEEE 22nd International Symposium on Personal, Indoor and Mobile Radio Communications.

[13]  Jens Zander,et al.  On the cost structure of future wideband wireless access , 1997, 1997 IEEE 47th Vehicular Technology Conference. Technology in Motion.

[14]  K. Johansson Cost Effective Deployment Strategies for Heterogenous Wireless Networks , 2007 .

[15]  Jean-Marie Gorce,et al.  Interference Modeling in CSMA Multi-Hop Wireless Networks , 2008 .

[16]  Sean A. Ramprashad,et al.  Rethinking network MIMO: Cost of CSIT, performance analysis, and architecture comparisons , 2010, 2010 Information Theory and Applications Workshop (ITA).

[17]  Renato M. de Moraes,et al.  Modeling Interference in Wireless Ad Hoc Networks , 2007, 2007 15th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems.

[18]  Ekram Hossain,et al.  Radio Resource Management in Wireless Networks , .

[19]  Harish Viswanathan,et al.  Self-Organizing Dynamic Fractional Frequency Reuse in OFDMA Systems , 2008, IEEE INFOCOM 2008 - The 27th Conference on Computer Communications.

[20]  Anders Furuskar,et al.  A Methodology for Estimating cost and Performance of Heterogeneous Wireless Access Networks Special Session Paper , 2007, 2007 IEEE 18th International Symposium on Personal, Indoor and Mobile Radio Communications.

[21]  Yung Yi,et al.  REFIM: A Practical Interference Management in Heterogeneous Wireless Access Networks , 2011, IEEE Journal on Selected Areas in Communications.

[22]  Marina Petrova,et al.  Wi-Fi, but not on Steroids: Performance analysis of a Wi-Fi-like Network operating in TVWS under realistic conditions , 2012, 2012 IEEE International Conference on Communications (ICC).

[23]  Reinaldo A. Valenzuela,et al.  Network coordination for spectrally efficient communications in cellular systems , 2006, IEEE Wireless Communications.

[24]  Jan Markendahl,et al.  A comparative study of deployment options, capacity and cost structure for macrocellular and femtocell networks , 2010, 2010 IEEE 21st International Symposium on Personal, Indoor and Mobile Radio Communications Workshops.

[25]  Michele Garetto,et al.  New insights into the stochastic geometry analysis of dense CSMA networks , 2011, 2011 Proceedings IEEE INFOCOM.

[26]  R. Ganti,et al.  Regularity, Interference, and Capacity of Large Ad Hoc Networks , 2006, 2006 Fortieth Asilomar Conference on Signals, Systems and Computers.

[27]  Andrea J. Goldsmith,et al.  On the optimality of multiantenna broadcast scheduling using zero-forcing beamforming , 2006, IEEE Journal on Selected Areas in Communications.

[28]  Max H. M. Costa,et al.  Writing on dirty paper , 1983, IEEE Trans. Inf. Theory.

[29]  Gerhard Fettweis,et al.  Increasing mobile rates while minimizing cost per bit — Cooperation vs. denser deployment , 2010, 2010 7th International Symposium on Wireless Communication Systems.

[30]  Morten Tolstrup Indoor Radio Planning: A Practical Guide for GSM, DCS, UMTS and HSPA , 2008 .

[31]  Umberto Spagnolini,et al.  Interference Coordination Vs. Interference Randomization in Multicell 3GPP LTE System , 2008, 2008 IEEE Wireless Communications and Networking Conference.

[32]  Afef Feki,et al.  Autonomous Spectrum Sharing for Mixed LTE Femto and Macro Cells Deployments , 2010, 2010 INFOCOM IEEE Conference on Computer Communications Workshops.

[33]  M. J. Gans,et al.  On Limits of Wireless Communications in a Fading Environment when Using Multiple Antennas , 1998, Wirel. Pers. Commun..

[34]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[35]  François Baccelli,et al.  Generating Functionals of Random Packing Point Processes: From Hard-Core to Carrier Sensing , 2012, ArXiv.

[36]  Martin Haenggi Outage and throughput bounds for stochastic wireless networks , 2005, Proceedings. International Symposium on Information Theory, 2005. ISIT 2005..

[37]  Shlomo Shamai,et al.  On the achievable throughput of a multiantenna Gaussian broadcast channel , 2003, IEEE Transactions on Information Theory.

[38]  Sean A. Ramprashad,et al.  Cellular vs. Network MIMO: A comparison including the channel state information overhead , 2009, 2009 IEEE 20th International Symposium on Personal, Indoor and Mobile Radio Communications.

[39]  Guillaume Chelius,et al.  Point processes for interference modeling in CSMA/CA ad-hoc networks , 2009, PE-WASUN '09.

[40]  Wei Yu,et al.  Multi-Cell MIMO Cooperative Networks: A New Look at Interference , 2010, IEEE Journal on Selected Areas in Communications.