When mmWave Communications Meet Network Densification: A Scalable Interference Coordination Perspective

Abstract

The millimeter-wave (mmWave) communication is envisioned to provide orders of magnitude capacity improvement. However, it is challenging to realize a sufficient link margin due to high path loss and blockages. To address this difficulty, in this paper, we explore the potential gain of ultra-densification for enhancing mmWave communications from a network-level perspective. By deploying the mmWave base stations (BSs) in an extremely dense and amorphous fashion, the access distance is reduced and the choice of serving BSs is enriched for each user, which are intuitively effective for mitigating the propagation loss and blockages. Nevertheless, co-channel interference under this model will become a performance-limiting factor. To solve this problem, we propose a large-scale channel state information (CSI) based interference coordination approach. Note that the large-scale CSI is highly location-dependent, and can be obtained with a quite low cost. Thus, the scalability of the proposed coordination framework can be guaranteed. Particularly, using only the large-scale CSI of interference links, a coordinated frequency resource block allocation problem is formulated for maximizing the minimum achievable rate of the users, which is uncovered to be a NP-hard integer programming problem. To circumvent this difficulty, a greedy scheme with polynomial-time complexity is proposed by adopting the bisection method and linear integer programming tools. Simulation results demonstrate that the proposed coordination scheme based on large-scale CSI only can still offer substantial gains over the existing methods. Moreover, although the proposed scheme is only guaranteed to converge to a local optimum, it performs well in terms of both user fairness and system efficiency.Index Terms-Millimeter-wave (mmWave) communication, network densification, interference coordination, large-scale channel state information (CSI), linear integer programming.

Millimeter Wave Communications for Future Mobile Networks

“…To meet the aggressive 5G KPIs discussed in Section I, an UDN deployment is considered as a promising system architecture to enable Gbps user experience and seamless coverage in mobile networks [235], [236]. In other words, many small-cell BSs are densely deployed as hotspots (e.g., in office buildings, shopping malls, residential apartments) that would greatly offload the macro cells.…”

Maritime Coverage Enhancement Using UAVs Coordinated With Hybrid Satellite-Terrestrial Networks

“…1) Optimization of transmit power: By using c l−1 a,t obtained in the (l − 1)-th iteration, we set c l a,t = c l−1 a,t , and optimize the transmit power P l a,t by solving the following problem max P l a,t ,Q l Q l (42) subject to (13), (14), (31), (38), (39).…”

“…In the m-th iteration, let U m−1 and L m−1 respectively denote the upper bound and lower bound of Q l . For Q m = U m−1 + L m−1 2, with given c l−1 a,t , v l−1 a,t April 5, 2019 DRAFT and P l a,t obtained by solving the problem in (42), the convex problem can be formulated as find c m a,t , v m a,t , a m a,t (44) subject to (10), (11), (12), (23), (24), (31), (37), (38), (39) where P a,t , c a,t , v a,t , a a,t , Q are replaced with P l a,t , c m a,t , v m a,t , a m a,t , Q m , respectively. Besides, v r a,t and c r a,t are replaced with v l−1 a,t and c l−1 a,t , respectively.…”

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“…Coupling factors Problems Possible solutions UDenseNets and mmWave [9] Large network throughput and mmWave signals travel short distance due to large propagation loss; hence, they are a good fit for UDenseNets…”