This paper studies a resource allocation problem where a set of users within a specific region is served by cloud radio access network (C-RAN) structure consisting of a set of base-band units (BBUs) connected to a set of radio remote heads (RRHs) equipped with a large number of antennas via limited capacity front-haul links. User association to each RRH, BBU and front-haul link is essential to achieve high rates for cell-edge users under network limitations. We introduce two types of optimization variables to formulate this resource allocation problem: (i) C-RAN user association factor (UAF) including RRH, BBU and front-haul allocation for each user and (ii) power allocation vector. The formulated optimization problem is non-convex with high computational complexity. An efficient two-level iterative approach is proposed. The higher level consists of two steps where, in each step, one of these two optimization variables is fixed to derive the other. At the lower level, by applying different transformations and convexification techniques, the optimization problem in each step is broken down into a sequence of geometric programming (GP) problems to be solved by the successive convex approximation (SCA). Simulation results reveal the effectiveness of the proposed approach to increase the total throughput of network, specifically for cell-edge users. It outperforms the traditional user association approach, in which, each user is first assigned to the RRH with the largest average value of signal strength, and then, based on this fixed user association, front-haul link association and power allocation are optimized.
Due to the increasing demand for mobile traffic, the unlicensed band operation for LTE is proposed by mobile operators. Although by using this approach higher capacity can be achieved for LTE, performance of other wireless technologies operating in this band such as WiFi can be degraded significantly. In order to enable efficient LTE/WiFi coexistence, we consider a coordinated structure via a virtual network entity. LTE users can transmit in the assigned time-slots, while WiFi users can compete with each other by using-persistent CSMA in their exclusive time-share. In an unsaturated network, at each duty cycle, the TDMA scheduling for LTE users and values for WiFi users are updated to maximize the overall network throughput subject to a constraint on the minimum acceptable throughput for WiFi. The corresponding optimization problem is formulated and an iterative algorithm is developed to find the optimal solution using complementary geometric programming (CGP) and monomial approximations. The simulation results reveal the performance gains of the proposed algorithm in preserving the WiFi throughput requirement.
In this paper, we present a reconfigurable MAC scheme where the partition between contention-free and contention-based regimes in each frame is adaptive to the network status leveraging reinforcement learning. In particular, to support a virtualized wireless network consisting of multiple slices, each having heterogeneous and unsaturated devices, the proposed scheme aims to configure the partition for maximizing network throughput while maintaining the slice reservations. Applying complementary geometric programming (CGP) and monomial approximations, an iterative algorithm is developed to find the optimal solution. For a large number of devices, a scalable algorithm with lower computational complexity is also proposed. The partitioning algorithm requires the knowledge of the device traffic statistics. In the absence of such knowledge, we develop a learning algorithm employing Thompson sampling to acquire packet arrival probabilities of devices. Furthermore, we model the problem as a thresholding multi-armed bandit (TMAB) and propose a threshold-based reconfigurable MAC algorithm, which is proved to achieve the optimal regret bound.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.