A Network-Assisted Approach for RAT Selection in Heterogeneous Cellular Networks (bibtex)
by Melhem El Helou, Marc Ibrahim, Samer Lahoud, Kinda Khawam, Dany Mezher, Bernard Cousin
Abstract:
When several radio access technologies (e.g., HSPA, LTE, WiFi, and WiMAX) cover the same region, deciding to which one mobiles connect is known as the Radio Access Technology (RAT) selection problem. To reduce network signaling and processing load, decisions are generally delegated to mobile users. Mobile users aim to selfishly maximize their utility. However, as they do not cooperate, their decisions may lead to performance inefficiency. In this paper, to overcome this limitation, we propose a network-assisted approach. The network provides information for the mobiles to make more accurate decisions. By appropriately tuning network information, user decisions are globally expected to meet operator objectives, avoiding undesirable network states. Deriving network information is formulated as a semi-Markov decision process (SMDP), and optimal policies are computed using the Policy Iteration algorithm. Also, and since network parameters may not be easily obtained, a reinforcement learning approach is introduced to derive what to signal to mobiles. The performances of optimal, learning-based, and heuristic policies, such as blocking probability and average throughput, are analyzed. When tuning thresholds are pertinently set, our heuristic achieves performance very close to the optimal solution. Moreover, although it provides lower performance, our learning-based algorithm has the crucial advantage of requiring no prior parameterization.
Reference:
A Network-Assisted Approach for RAT Selection in Heterogeneous Cellular Networks (Melhem El Helou, Marc Ibrahim, Samer Lahoud, Kinda Khawam, Dany Mezher, Bernard Cousin), In IEEE Journal on Selected Areas in Communications - Special Issue on Recent Advances in Heterogenous Cellular Networks (JSAC - HCN), volume 33, 2015.
Bibtex Entry:
@Article{	  el-helou:2015cr,
  abstract	= {When several radio access technologies (e.g., HSPA, LTE,
		  WiFi, and WiMAX) cover the same region, deciding to which
		  one mobiles connect is known as the Radio Access Technology
		  (RAT) selection problem. To reduce network signaling and
		  processing load, decisions are generally delegated to
		  mobile users. Mobile users aim to selfishly maximize their
		  utility. However, as they do not cooperate, their decisions
		  may lead to performance inefficiency. In this paper, to
		  overcome this limitation, we propose a network-assisted
		  approach. The network provides information for the mobiles
		  to make more accurate decisions. By appropriately tuning
		  network information, user decisions are globally expected
		  to meet operator objectives, avoiding undesirable network
		  states. Deriving network information is formulated as a
		  semi-Markov decision process (SMDP), and optimal policies
		  are computed using the Policy Iteration algorithm. Also,
		  and since network parameters may not be easily obtained, a
		  reinforcement learning approach is introduced to derive
		  what to signal to mobiles. The performances of optimal,
		  learning-based, and heuristic policies, such as blocking
		  probability and average throughput, are analyzed. When
		  tuning thresholds are pertinently set, our heuristic
		  achieves performance very close to the optimal solution.
		  Moreover, although it provides lower performance, our
		  learning-based algorithm has the crucial advantage of
		  requiring no prior parameterization.},
  author	= {Melhem {El Helou} and Marc Ibrahim and Samer Lahoud and
		  Kinda Khawam and Dany Mezher and Bernard Cousin},
  doi		= {10.1109/JSAC.2015.2416987},
  issn		= {0733-8716},
  journal	= {IEEE Journal on Selected Areas in Communications - Special
		  Issue on Recent Advances in Heterogenous Cellular Networks
		  (JSAC - HCN)},
  keywords	= {Radio access technology selection; semi-Markov decision
		  process; reinforcement learning; heterogeneous cellular
		  networks},
  month		= {June},
  number	= {6},
  pages		= {1055-1067},
  pdf		= {http://samer.lahoud.fr/pub-pdf/jsac-15.pdf},
  title		= {A Network-Assisted Approach for {RAT} Selection in
		  Heterogeneous Cellular Networks},
  volume	= {33},
  year		= {2015}
}
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