Stability and Dynamic Control of Underlay Mobile Edge Networks

This paper studies the stability and dynamic control of underlay mobile edge networks. First, the stability region for a multiuser edge network is obtained under the assumption of full channel state information. This result provides a benchmark figure for comparing performance of the proposed algorithms. Second, a centralized joint flow control and scheduling algorithm is proposed to stabilize the queues of edge devices while respecting the average and instantaneous interference power constraints at the core access point. This algorithm is proven to converge to a utility point arbitrarily close to the maximum achievable utility within the stability region. Finally, more practical implementation issues such as distributed scheduling are examined by designing efficient scheduling algorithms taking advantage of communication diversity. The proposed distributed solutions utilize mini-slots for contention resolution and achieve a certain fraction of the utility optimal point. The performance lower bounds for distributed algorithms are determined analytically. The detailed simulation study is performed to pinpoint the cost of distributed control for mobile edge networks with respect to centralized control.

[1]  Koushik Kar,et al.  Cross-layer rate control for end-to-end proportional fairness in wireless networks with random access , 2005, MobiHoc '05.

[2]  Tamer A. ElBatt,et al.  Cognitive Radio Networks With Probabilistic Relaying: Stable Throughput and Delay Tradeoffs , 2015, IEEE Transactions on Communications.

[3]  Leandros Tassiulas,et al.  Resource Allocation and Cross-Layer Control in Wireless Networks , 2006, Found. Trends Netw..

[4]  Tao Zhang,et al.  Fog and IoT: An Overview of Research Opportunities , 2016, IEEE Internet of Things Journal.

[5]  Anthony Ephremides,et al.  Cooperation in Cognitive Underlay Networks: Stable Throughput Tradeoffs , 2014, IEEE/ACM Transactions on Networking.

[6]  Sooyong Choi,et al.  Joint Mode Selection and Power Allocation Scheme for Power-Efficient Device-to-Device (D2D) Communication , 2012, 2012 IEEE 75th Vehicular Technology Conference (VTC Spring).

[7]  Sungsoo Park,et al.  Capacity Enhancement Using an Interference Limited Area for Device-to-Device Uplink Underlaying Cellular Networks , 2011, IEEE Transactions on Wireless Communications.

[8]  Yusheng Ji,et al.  Resource allocation using particle swarm optimization for D2D communication underlay of cellular networks , 2013, 2013 IEEE Wireless Communications and Networking Conference (WCNC).

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

[10]  Eylem Ekici,et al.  Efficient distributed scheduling in cognitive radio networks in the many-channel regime , 2013, 2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt).

[11]  Frank Kelly,et al.  Rate control for communication networks: shadow prices, proportional fairness and stability , 1998, J. Oper. Res. Soc..

[12]  Stefan Parkvall,et al.  Design aspects of network assisted device-to-device communications , 2012, IEEE Communications Magazine.

[13]  Ian F. Akyildiz,et al.  5G roadmap: 10 key enabling technologies , 2016, Comput. Networks.

[14]  Xuemin Shen Device-to-device communication in 5G cellular networks , 2015, IEEE Network.

[15]  Long Bao Le Fair resource allocation for device-to-device communications in wireless cellular networks , 2012, 2012 IEEE Global Communications Conference (GLOBECOM).

[16]  Michael J. Neely,et al.  Opportunistic Scheduling with Reliability Guarantees in Cognitive Radio Networks , 2008, IEEE INFOCOM 2008 - The 27th Conference on Computer Communications.

[17]  Hazer Inaltekin,et al.  Throughput Analysis for the Cognitive Uplink Under Limited Primary Cooperation , 2016, IEEE Transactions on Communications.

[18]  Hazer Inaltekin,et al.  Power Control and Asymptotic Throughput Analysis for the Distributed Cognitive Uplink , 2014, IEEE Transactions on Communications.

[19]  Tao Chen,et al.  Device-To-Device (D2D) Communication in Cellular Network - Performance Analysis of Optimum and Practical Communication Mode Selection , 2010, 2010 IEEE Wireless Communication and Networking Conference.

[20]  Geoffrey Ye Li,et al.  Device-to-Device Communications Underlaying Cellular Networks , 2013, IEEE Transactions on Communications.

[21]  Olav Tirkkonen,et al.  On the Performance of Device-to-Device Underlay Communication with Simple Power Control , 2009, VTC Spring 2009 - IEEE 69th Vehicular Technology Conference.

[22]  Hans-Jürgen Zepernick,et al.  Outage probability and ergodic capacity of underlay cognitive radio systems with adaptive power transmission , 2013, 2013 9th International Wireless Communications and Mobile Computing Conference (IWCMC).

[23]  Trung Q. Duong,et al.  Queuing analysis for cognitive radio networks under peak interference power constraint , 2011, International Symposium on Wireless and Pervasive Computing.

[24]  D. Luenberger Optimization by Vector Space Methods , 1968 .

[25]  Jianhua Lu,et al.  A QoS-Aware Power Optimization Scheme in OFDMA Systems with Integrated Device-to-Device (D2D) Communications , 2011, 2011 IEEE Vehicular Technology Conference (VTC Fall).

[26]  Liping Wang,et al.  Dynamic Cooperative Secondary Access in Hierarchical Spectrum Sharing Networks , 2014, IEEE Transactions on Wireless Communications.

[27]  Giuseppe Caire,et al.  Wireless Device-to-Device Caching Networks: Basic Principles and System Performance , 2013, IEEE Journal on Selected Areas in Communications.

[28]  Andrea J. Goldsmith,et al.  Breaking Spectrum Gridlock With Cognitive Radios: An Information Theoretic Perspective , 2009, Proceedings of the IEEE.

[29]  John S. Thompson,et al.  Stability analysis for cognitive radio with multi-access primary transmission , 2010, IEEE Transactions on Wireless Communications.

[30]  Olav Tirkkonen,et al.  Device-to-Device Communication Underlaying Cellular Communications Systems , 2009, Int. J. Commun. Netw. Syst. Sci..

[31]  Michael J. Neely,et al.  Optimal Energy and Delay Tradeoffs for Multi-User Wireless Downlinks , 2006, Proceedings IEEE INFOCOM 2006. 25TH IEEE International Conference on Computer Communications.

[32]  Leandros Tassiulas,et al.  Asymptotic Laws for Joint Content Replication and Delivery in Wireless Networks , 2012, IEEE Transactions on Information Theory.

[33]  Hazer Inaltekin,et al.  Throughput Scaling in Cognitive Multiple Access With Average Power and Interference Constraints , 2012, IEEE Transactions on Signal Processing.