Performance of pico-cell clusters with cooperative receivers

Pico-cell clusters have been proposed for providing high capacities to dense sets of users in next generation networks. We consider the uplink channel and analyze the sum-rate performance of two interfering pico-cell clusters with cooperative multi-cell joint decoding (MJD). The performance of a linear receiver is compared with that of non-linear receivers which allow message passing between the clusters in order to cancel the associated interference. The receiver, in all the above cases, jointly processes all signals across a single cluster. However we consider different message passing schemes, and maximize the sum rate over system parameters, including the load in each cell. Our results are valid in the large-system limit as the number of cells and antennas per cluster each tend to infinity with fixed ratio. Numerical results show that the nonlinear receivers provide significantly larger capacities than linear receivers, especially at high SNRs.

[1]  Muhammad Ali Imran,et al.  Uplink capacity of a variable density cellular system with multicell processing , 2009, IEEE Transactions on Communications.

[2]  Symeon Chatzinotas,et al.  Free probability based capacity calculation of multiantenna Gaussian fading channels with cochannel interference , 2011, Phys. Commun..

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

[4]  Wolfgang Rave,et al.  Distributed Iterative Multiuser Detection through Base Station Cooperation , 2008, EURASIP J. Wirel. Commun. Netw..

[5]  Jakob Hoydis,et al.  Asymptotic performance of linear receivers in network MIMO , 2010, 2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers.

[6]  Symeon Chatzinotas,et al.  On the Capacity of Variable Density Cellular Systems under Multicell Decoding , 2008, IEEE Communications Letters.

[7]  Aaron D. Wyner,et al.  Shannon-theoretic approach to a Gaussian cellular multiple-access channel , 1994, IEEE Trans. Inf. Theory.

[8]  Shlomo Shamai,et al.  Shannon-theoretic approach to a Gaussian cellular multiple-access channel with fading , 2000, IEEE Trans. Inf. Theory.

[9]  Shlomo Shamai,et al.  Multicell uplink spectral efficiency of coded DS-CDMA with random signatures , 2001, IEEE J. Sel. Areas Commun..

[10]  Michael L. Honig,et al.  Multi-cell distributed interference cancellation for Co-operative Pico-cell clusters , 2012, 2012 IEEE Global Communications Conference (GLOBECOM).

[11]  Shlomo Shamai,et al.  Sum Rate Characterization of Joint Multiple Cell-Site Processing , 2007, IEEE Transactions on Information Theory.

[12]  P. Whiting,et al.  Information-theoretic capacity of multi-receiver networks , 1993, Telecommun. Syst..

[13]  Symeon Chatzinotas,et al.  Clustered Multicell Joint Decoding under Cochannel Interference , 2011, 2011 IEEE International Conference on Communications (ICC).

[14]  S. Chatzinotas,et al.  Optimal information theoretic capacity of the planar cellular uplink channel , 2008, 2008 IEEE 9th Workshop on Signal Processing Advances in Wireless Communications.

[15]  Iain B. Collings,et al.  Performance with Random Signatures , 2009 .

[16]  Antonia Maria Tulino,et al.  Random Matrix Theory and Wireless Communications , 2004, Found. Trends Commun. Inf. Theory.

[17]  R. Couillet,et al.  Random Matrix Methods for Wireless Communications: Estimation , 2011 .