TY - JOUR

T1 - Heterogeneous Cellular Networks Using Wireless Backhaul

T2 - Fast Admission Control and Large System Analysis

AU - Zhao, Jian

AU - Quek, Tony Q.S.

AU - Lei, Zhongding

N1 - Publisher Copyright:
© 1983-2012 IEEE.

PY - 2015/10/1

Y1 - 2015/10/1

N2 - We consider a heterogeneous cellular network with densely underlaid small cell access points (SAPs). Wireless backhaul provides the data connection from the core network to SAPs. To serve as many SAPs and their corresponding users as possible with guaranteed data rates, admission control of SAPs needs to be performed in wireless backhaul. Such a problem involves joint design of transmit beamformers, power control, and selection of SAPs. In order to tackle such a difficult problem, we apply $\ell-1$-relaxation and propose an iterative algorithm for the $\ell-1$-relaxed problem. The selection of SAPs is made based on the outputs of the iterative algorithm, and we prove such an algorithm converges locally. Furthermore, this algorithm is fast and enjoys low complexity for small-to-medium sized systems. However, its solution depends on the actual channel state information, and resuming the algorithm for each new channel realization may be unrealistic for large systems. Therefore, we make use of the random matrix theory and also propose an iterative algorithm for large systems. Such a large-system iterative algorithm can produce the asymptotically optimum solution for the $\ell-1$-relaxed problem, which only requires large-scale channel coefficients irrespective of the actual channel realization. Near optimum results are achieved by our proposed algorithms in simulations.

AB - We consider a heterogeneous cellular network with densely underlaid small cell access points (SAPs). Wireless backhaul provides the data connection from the core network to SAPs. To serve as many SAPs and their corresponding users as possible with guaranteed data rates, admission control of SAPs needs to be performed in wireless backhaul. Such a problem involves joint design of transmit beamformers, power control, and selection of SAPs. In order to tackle such a difficult problem, we apply $\ell-1$-relaxation and propose an iterative algorithm for the $\ell-1$-relaxed problem. The selection of SAPs is made based on the outputs of the iterative algorithm, and we prove such an algorithm converges locally. Furthermore, this algorithm is fast and enjoys low complexity for small-to-medium sized systems. However, its solution depends on the actual channel state information, and resuming the algorithm for each new channel realization may be unrealistic for large systems. Therefore, we make use of the random matrix theory and also propose an iterative algorithm for large systems. Such a large-system iterative algorithm can produce the asymptotically optimum solution for the $\ell-1$-relaxed problem, which only requires large-scale channel coefficients irrespective of the actual channel realization. Near optimum results are achieved by our proposed algorithms in simulations.

UR - http://www.scopus.com/inward/record.url?scp=84942311399&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84942311399&partnerID=8YFLogxK

U2 - 10.1109/JSAC.2015.2439471

DO - 10.1109/JSAC.2015.2439471

M3 - Article

AN - SCOPUS:84942311399

VL - 33

SP - 2128

EP - 2143

JO - IEEE Journal on Selected Areas in Communications

JF - IEEE Journal on Selected Areas in Communications

SN - 0733-8716

IS - 10

M1 - 7115025

ER -