Joint Load Balancing and Interference Mitigation in 5G Heterogeneous Networks

• Published in: IEEE transactions on wireless communications Vol. 16; no. 9; pp. 6032 - 6046
• Main Authors: Trung Kien Vu, Bennis, Mehdi, Samarakoon, Sumudu, Debbah, Merouane, Latva-aho, Matti
• Format: Journal Article
• Language: English
• Published: IEEE 01.09.2017; Institute of Electrical and Electronics Engineers
• Subjects: 5G mobile communication; Engineering Sciences; full-duplex; imperfect CSI; Interference; Load management; Massive MIMO; MIMO; mm-wave communications; non-convex optimization; random matrix theory; self-backhaul; Transmitting antennas; ultra dense small cells; Wireless communication
• ISSN: 1536-1276
• DOI: 10.1109/TWC.2017.2718504

We study the problem of joint load balancing and interference mitigation in heterogeneous networks in which massive multiple-input multiple-output macro cell base station (BS) equipped with a large number of antennas, overlaid with wireless self-backhauled small cells (SCs), is assumed. Self-backhauled SC BSs with full-duplex communication employing regular antenna arrays serve both macro users and SC users by using the wireless backhaul from macro BS in the same frequency band. We formulate the joint load balancing and interference mitigation problem as a network utility maximization subject to wireless backhaul constraints. Subsequently, leveraging the framework of stochastic optimization, the problem is decoupled into dynamic scheduling of macro cell users, backhaul provisioning of SCs, and offloading macro cell users to SCs as a function of interference and backhaul links. Via numerical results, we show the performance gains of our proposed framework under the impact of SCs density, number of BS antennas, and transmit power levels at low and high frequency bands. It is shown that our proposed approach achieves a 5.6 times gain in terms of cell-edge performance as compared with the closed-access baseline in ultra-dense networks with 350 SC BSs per km 2 .