Abstract: Traditional cellular networks require the downlink (DL) and uplink (UL) of mobile users (MUs) to be associated with a single base station (BS). However, the power gap between BSs and MUs in different transmission environments results in the BS with the strongest downlink differing from the BS with the strongest uplink. In addition, the significant increase in the number of wireless machine type communication (MTC) devices accessing cellular networks has created a DL/UL traffic imbalance with higher traffic volume on the uplink. In this paper, a joint user association and resource partition framework for downlink-uplink decoupling (DUDe) is developed for a tiered heterogeneous cellular network (HCN). Different from the traditional association rules such as maximal received power and range extension, a coalition game based scheme is proposed for the optimal user association with DUDe. The stability and convergence of this scheme are proven and shown to converge to a Nash equilibrium at a geometric rate. Moreover, the DL and UL optimal bandwidth partition for BSs is derived based on user association considering fairness. Extensive simulation results demonstrate the effectiveness of the proposed scheme, which enhances the sum rate compared with other user association strategies.

多层异构蜂窝网络上下行解耦的联合用户接入与资源划分

[1]Andrews, J.G., 2013. Seven ways that HetNets are a cellular paradigm shift. IEEE Commun. Mag., 51(3):136-144.

[2]Boccardi, F., Andrews, J., Elshaer, H., et al., 2016. Why to decouple the uplink and downlink in cellular networks and how to do it. IEEE Commun. Mag., 54(3):110-117.

[3]Brémaud, P., 1999. Markov Chains: Gibbs Fields, Monte Carlo Simulation, and Queues. Springer-Verlag, New York, NY.

[4]Dhillon, H.S., Ganti, R.K., Baccelli, F., et al., 2012. Modeling and analysis of k-tier downlink heterogeneous cellular networks. IEEE J. Sel. Areas Commun., 30(3):556-560.

[5]Dhillon, H.S., Ganti, R.K., Andrews, J.G., 2013. Load-aware modeling and analysis of heterogeneous cellular networks. IEEE Trans. Wirel. Commun., 12(4):1666-1677.

[6]ElSawy, H., Hossain, E., Haenggi, M., 2013. Stochastic geometry for modeling, analysis, and design of multi-tier and cognitive cellular wireless networks: a survey. IEEE Commun. Surv. Tutor., 15(3):996-1019.

[7]Elshaer, H., Boccardi, F., Dohler, M., et al., 2014. Downlink and uplink decoupling: a disruptive architectural design for 5G networks. Proc. IEEE Globecom, p.1798-1803.

[8]Feng, Z., Feng, Z., Li, W., et al., 2014. Downlink and uplink splitting user association in two-tier heterogeneous cellular networks. Proc. IEEE Globecom, p.4659-4664.

[9]Fooladivanda, D., Rosenberg, C., 2013. Joint resource allocation and user association for heterogeneous wireless cellular networks. IEEE Trans. Wirel. Commun., 12(1):248-257.

[10]Ge, X., Tu, S., Mao, G., et al., 2016. 5G ultra-dense cellular networks. IEEE Wirel. Commun., 23(1):72-79.

[11]Jiang, L., Sha, X., Wu, X., et al., 2016. A novel resource allocation algorithm based on downlink and uplink decouple access scheme in heterogeneous networks. China Commun., 13(6):1673-5447.

[12]Jo, H.S., Sang, Y.J., Xia, P., et al., 2012. Heterogeneous cellular networks with flexible cell association: a comprehensive downlink SINR analysis. IEEE Trans. Wirel. Commun., 11(10):3484-3495.

[13]Li, Y., Jin, D., Yuan, J., et al., 2014. Coalitional games for resource allocation in the device-to-device uplink underlaying cellular networks. IEEE Trans. Wirel. Commun., 13(7):3965-3977.

[14]Lien, S., Chen, K., Lin, Y., 2011. Toward ubiquitous massive accesses in 3GPP machine-to-machine communications. IEEE Commun. Mag., 49(4):66-74.

[15]López-Pérez, D., Güvenc, .I., Roche, G., et al., 2011. Enhanced intercell interference coordination challenges in heterogeneous networks. IEEE Wirel. Commun., 18(3):22-30.

[16]Madan, R., Borran, J., Sampath, A., et al., 2010. Cell association and interference coordination in heterogeneous LTE-A cellular networks. IEEE J. Sel. Areas Commun., 28(9):1479-1489.

[17]Nesterov, Y., Nemirovski, A., 1994. Interior point polynomial time methods in convex programming. In: SIAM Studies in Applied Mathematics. Philadelphia, PA.

[18]Saad, W., Han, Z., Hjo rungnes, A., 2011. Coalitional games for cooperative wireless cellular networks. In: Hossain, E., Kim, D., Bhargava, V. (Eds.), Cooperative Cellular Wireless Networks. Cambridge University Press.

[19]Singh, S., Baccelli, F., Andrews, J.G., 2014. On association cells in random heterogeneous networks. IEEE Wirel. Commun. Lett., 3(1):70-73.

[20]Singh, S., Zhang, X., Andrews, J.G., 2015. Joint rate and SINR coverage analysis for decoupled uplink-downlink biased cell associations in HetNets. IEEE Trans. Wirel. Commun., 14(10):5360-5373.

[21]Smiljkovikj, K., Popovski, P., Gavrilovska, L., 2015. Analysis of the decoupled access for downlink and uplink in wireless heterogeneous networks. IEEE Wirel. Commun. Lett., 4(2):173-176.

[22]Son, K., Kim, H., Yi, Y., et al., 2011. Base station operation and user association mechanisms for energy-delay tradeoffs in green cellular networks. IEEE J. Sel. Areas Commun., 29(8):1525-1536.

[23]Yang, C., Li, J., Guizani, M., 2016. Cooperation for spectral and energy efficiency in ultra-dense small cell networks. IEEE Wirel. Commun., 23(1):64-71.

[24]Ye, Q., Rong, B., Chen, Y., et al., 2013. User association for load balancing in heterogeneous cellular networks. IEEE Trans. Wirel. Commun., 12(6):2706-2716.