Research on Resource Efficiency Optimization Model of TDMA-Based Distributed Wireless Ad Hoc Networks

Because of networking flexibility, strong robustness and expansibility, and low cost of operation and maintenance, distributed wireless ad hoc networks are widely used in ultra-density 5th-Generation (5G) networks, Device to Device (D2D) communications and industrial wireless sensor networks. However, compared with the centralized ones, the Time Division Multiple Access(TDMA)-based distributed network lacks centralized coordination by a control center, while its resource scheduling only depends on partial information, and the high receiving failure probability caused by neighbors’ cumulative interference outside the scope of maintenance may reduce the resource efficiency and restrict its usability according to the existing protocols severely. The simulation results show that the transmission failure probability can be up to 20% when maintaining two-hops neighbors in TDMA-based coordinated distributed scheduling. But the research on the cumulative interference outside the scope of maintenance and the optimal neighbor maintenance scope is still unclear at present. In this paper, we establish a resource efficiency model and an interference model of control messages and data messages under different neighbor maintenance by hardcore point process (HCPP) considering cumulative interference, cost of Media Access Control (MAC) layer and channel multiplex. Furtherly, we build an optimization model to maximize the resource efficiency under scheduling delay and receiving success probability constraints, thus we can obtain the optimal scope of maintenance in different network conditions. We conduct extensive theoretical analysis and simulations to evaluate the correctness of models. Simulation results show that the resource efficiency optimization model can provide guidance for optimal protocol parameters design.

[1]  Abbas Jamalipour,et al.  Energy efficiency of combined DPS and JT CoMP technique in downlink LTE-A cellular networks , 2016, 2016 IEEE International Conference on Communications (ICC).

[2]  Yang Jie,et al.  Performance Analysis of Two-Tier Heterogeneous Cellular Networks Based on Poisson Hard-Core Process , 2019, 2019 IEEE 19th International Conference on Communication Technology (ICCT).

[3]  Wei Zheng,et al.  K-Floors HCPP Model Based Performance Analysis of Indoor Ultra-Dense WLANs , 2018, 2018 IEEE International Conference on Communications Workshops (ICC Workshops).

[4]  Symeon Chatzinotas,et al.  Performance Analysis of Cell-Free Massive MIMO Systems: A Stochastic Geometry Approach , 2020, IEEE Transactions on Vehicular Technology.

[5]  Robert C. Elliott,et al.  Empirical Distribution of Nearest-Transmitter Distance in Wireless Networks Modeled by Matérn Hard Core Point Processes , 2018, IEEE Transactions on Vehicular Technology.

[6]  Dusit Niyato,et al.  Modeling and analysis of wireless networks using poisson hard-core process , 2017, 2017 IEEE International Conference on Communications (ICC).

[7]  Dusit Niyato,et al.  Analysis of Heterogeneous Wireless Networks Using Poisson Hard-Core Hole Process , 2017, IEEE Transactions on Wireless Communications.

[8]  Martin Haenggi,et al.  Mean Interference in Hard-Core Wireless Networks , 2011, IEEE Communications Letters.

[9]  Martin Haenggi,et al.  Stochastic Geometry for Wireless Networks , 2012 .

[10]  Minghua Chen,et al.  Capacity of Large-Scale CSMA Wireless Networks , 2009, IEEE/ACM Transactions on Networking.

[11]  Xiaohu Ge,et al.  Energy Efficiency of Multiuser Multiantenna Random Cellular Networks With Minimum Distance Constraints , 2017, IEEE Transactions on Vehicular Technology.

[12]  Liqun Fu,et al.  Hidden-Node Problem in Full-Duplex Enabled CSMA Networks , 2020, IEEE Transactions on Mobile Computing.

[13]  Y. Li,et al.  Delay and throughput performance of IEEE 802.16 WiMax mesh networks , 2012, IET Commun..

[14]  S.R. Mangalwede,et al.  Centralized scheduling and efficient channel assignment algorithm in Wireless Mesh Networks , 2016, 2016 2nd International Conference on Applied and Theoretical Computing and Communication Technology (iCATccT).

[15]  Hua Zhu,et al.  On The Interference Modeling Issues for Coordinated Distributed Scheduling in IEEE 802.16 Mesh Networks , 2006, 2006 3rd International Conference on Broadband Communications, Networks and Systems.

[16]  Gianluigi Ferrari,et al.  Ad Hoc Wireless Networks: A Communication-Theoretic Perspective , 2006 .

[17]  Daisuke Takita Centralized scheduling for wireless mesh networks with contention-reduced media access , 2013, 2013 International Symposium on Intelligent Signal Processing and Communication Systems.

[18]  Riku Jäntti,et al.  Bounding the Mean Interference in Mat\'ern Type II Hard-Core Wireless Networks , 2013, IEEE Wireless Communications Letters.

[19]  Minglei Shu,et al.  Throughput assurance of wireless body area networks coexistence based on stochastic geometry , 2017, PloS one.

[20]  Xu Li,et al.  Performance modeling and analysis of distributed multi-hop wireless ad hoc networks , 2016, 2016 IEEE International Conference on Communications (ICC).

[21]  Robin J. Evans,et al.  Nearest Neighbor Distance Distribution in Hard-Core Point Processes , 2016, IEEE Communications Letters.

[22]  Soung Chang Liew,et al.  Effective Static and Adaptive Carrier Sensing for Dense Wireless CSMA Networks , 2017, IEEE Transactions on Mobile Computing.

[23]  Denis N. Fakhriev,et al.  Transmission of real-time traffic in TDMA multi-hop wireless ad-hoc networks , 2015, 2015 IEEE International Conference on Communications (ICC).

[24]  Ness B. Shroff,et al.  Understanding the Capacity Region of the Greedy Maximal Scheduling Algorithm in Multihop Wireless Networks , 2008, IEEE/ACM Transactions on Networking.