On the scaling of interference alignment under delay and power constraints

Future wireless standards such as 5G envision dense wireless networks with large number of simultaneously connected devices. In this context, interference management becomes critical in achieving high spectral efficiency. Orthogonal signaling, which limits the number of users utilizing the resource simultaneously, gives a sum-rate that remains constant with increasing number of users. An alternative approach called interference alignment promises a throughput that scales linearly with the number of users. However, this approach requires very high SNR or long time duration for sufficient channel variation, and therefore may not be feasible in real wireless systems. We explore ways to manage interference in large networks with delay and power constraints. Specifically, we devise an interference phase alignment strategy that combines precoding and scheduling without using power control to exploit the diversity inherent in a system with large number of users. We show that this scheme achieves a sum-rate that scales almost logarithmically with the number of users. We also show upper bounds on the sum-rate within the restricted class of single-symbol phase alignment schemes. Specifically, we prove that no scheme in this class can achieve better than logarithmic scaling of the sum-rate.

[1]  Ayfer Özgür,et al.  Channel Diversity Needed for Vector Space Interference Alignment , 2014, IEEE Transactions on Information Theory.

[2]  Ayfer Özgür,et al.  Achieving linear scaling with interference alignment , 2009, 2009 IEEE International Symposium on Information Theory.

[3]  Sriram Vishwanath,et al.  Ergodic Interference Alignment , 2009, IEEE Transactions on Information Theory.

[4]  Syed Ali Jafar The Ergodic Capacity of Phase-Fading Interference Networks , 2011, IEEE Transactions on Information Theory.

[5]  Zhi-Quan Luo,et al.  On the Degrees of Freedom Achievable Through Interference Alignment in a MIMO Interference Channel , 2011, IEEE Transactions on Signal Processing.

[6]  S. Parkvall,et al.  Evolving Wireless Communications: Addressing the Challenges and Expectations of the Future , 2013, IEEE Vehicular Technology Magazine.

[7]  Ayfer Özgür,et al.  Channel diversity needed for vector interference alignment , 2014, 2014 IEEE International Symposium on Information Theory.

[8]  Syed Ali Jafar,et al.  Interference Alignment and Degrees of Freedom of the $K$-User Interference Channel , 2008, IEEE Transactions on Information Theory.

[9]  Taoka Hidekazu,et al.  Scenarios for 5G mobile and wireless communications: the vision of the METIS project , 2014, IEEE Communications Magazine.

[10]  Panganamala Ramana Kumar,et al.  RHEINISCH-WESTFÄLISCHE TECHNISCHE HOCHSCHULE AACHEN , 2001 .

[11]  Ayfer Özgür,et al.  Hierarchical Cooperation Achieves Optimal Capacity Scaling in Ad Hoc Networks , 2006, IEEE Transactions on Information Theory.

[12]  Guy Bresler,et al.  3 User interference channel: Degrees of freedom as a function of channel diversity , 2009, 2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

[13]  Eli Upfal,et al.  Probability and Computing: Randomized Algorithms and Probabilistic Analysis , 2005 .

[14]  Amir K. Khandani,et al.  Real Interference Alignment: Exploiting the Potential of Single Antenna Systems , 2009, IEEE Transactions on Information Theory.

[15]  B. Bollobás,et al.  Cliques in random graphs , 1976, Mathematical Proceedings of the Cambridge Philosophical Society.

[16]  Aria Nosratinia,et al.  The multiplexing gain of wireless networks , 2005, Proceedings. International Symposium on Information Theory, 2005. ISIT 2005..

[17]  M. M. Dodson,et al.  Diophantine approximation, Khintchine's theorem, torus geometry and Hausdorff dimension , 2007, 0710.4264.

[18]  G. Grimmett,et al.  On colouring random graphs , 1975 .

[19]  V. Cadambe,et al.  Interference alignment with asymmetric complex signaling , 2009, 2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

[20]  Ali Tajer,et al.  (n, K)-user interference channels: Degrees of freedom , 2011, 2011 IEEE International Symposium on Information Theory Proceedings.

[21]  Syed Ali Jafar,et al.  Interference Alignment With Asymmetric Complex Signaling—Settling the Høst-Madsen–Nosratinia Conjecture , 2009, IEEE Transactions on Information Theory.