Learning-Based Uplink Interference Management in 4G LTE Cellular Systems

Abstract

LTE's uplink (UL) efficiency critically depends on how the interference across different cells is controlled. The unique characteristics of LTE's modulation and UL resource assignment poses considerable challenges in achieving this goal because most LTE deployments have 1:1 frequency re-use, and the uplink interference can vary considerably across successive time slots. In this work, we propose LeAP, a measurement datadriven machine learning paradigm for power control to manage uplink interference in LTE. The data driven approach has the inherent advantage that the solution adapts based on network traffic, propagation and network topology, that is increasingly heterogeneous with multiple cell-overlays. LeAP system design consists of the following components: (i) design of user equipment (UE) measurement statistics that are succinct, yet expressive enough to capture the network dynamics, and (ii) design of two learning based algorithms that use the reported measurements to set the power control parameters and optimize the network performance. LeAP is standards compliant and can be implemented in centralized SON (self organized networking) server resource (cloud). We perform extensive evaluations using radio network plans from real LTE network operational in a major metro area in United States. Our results show that, compared to existing approaches, LeAP provides 4.9× gain in the 20 th % − tile of user data rate, 3.25× gain in median data rate.of User-U in the same frequency block as User-A, and, 1 1 1 U , U ∈ {B, C, D, E} is an 0 − 1 indicator variable denoting whether User-U also transmits over the same time-frequency block as User-A. Note that, since User-B and User-C share the same cell, only one of them can be active in a time-frequency resource and thus 1 1 1 B +1 1 1 C ≤ 1; similarly 1 1 1 D +1 1 1 E ≤ 1. Since MAC of each neighboring cell makes independent scheduling decision on who gets scheduled in a time-frequency block, the interference becomes highly unpredictable from transmission to transmission; managing this unstable interference pattern poses unique research challenges barely addressed in the literature. Indeed, this is unlike 3G systems 2 , where the neighboring cell interference for a similar topology with CDMA technology (over an appropriate CDMA channel) would simply be Int A (CDM A) = P B + P C + P D + P E thus leading to a more stable interference pattern across transmissions. In general, unlike LTE, the overall CDMA uplink interference also has an additional term for self cell interference due to uplink users in the same cell. Of course, for desirable user performance, the uplink interference still has to be managed through power control algorithms that has been the focus of much of the existing research on 3G power control and uplink interference management.Solution requirements: LTE networks are deployed with self organized networking (SON) capabilities [1], [2] to maximize network performances. Today's LTE networks are also heterogeneous (HTNs) that include high power macro cells overlay...

Wireless-Uplinks-Based Energy-Efficient Scheduling in Mobile Cloud Computing

“…In [22], Liu et al proposed a dynamic carrier aggregation (DCA) scheme to improve the energy efficiency of uplink communications. In [23], Deb and Monogioudis proposed LeAP, a measurement data-driven machine learning paradigm for power control to manage uplink interference in LTE. The authors in [11] derived the energy-efficient scheduling automatically select channels and requires channel state information to decide whether and when to defer data uploading.…”

Analysis of a Frequency-Hopping Millimeter-Wave Cellular Uplink

“…However, the basic structure of the fourth-generation (4G) single-carrier frequency-division multiple-access (SC-FDMA) uplink systems will likely be maintained due to the critical importance of transmitter power efficiency, which is enabled by the low peak-to-average power ratio of SC-FDMA and similar single-channel modulations [3], [4]. It is also likely that 5G systems will exploit frequency hopping to compensate for frequency-selective fading and to randomize out-of-cell interference, as is done in 4G systems [5].…”

Power headroom report-based uplink power control in 3GPP LTE-A HetNet

“…In a 3rd Generation Partnership Project Long Term Evolution-Advanced (3GPP LTE-A) uplink, the orthogonality provided by single carrier-frequency division multiple access (SC-FDMA) removes intra-cell interference-i.e., the interference between users in the same cell [1]. However, the inter-cell interference problem remains to be solved because the band allocated to a user in a cell can be used by another user in any of the neighboring cells.…”

“…However, the inter-cell interference problem remains to be solved because the band allocated to a user in a cell can be used by another user in any of the neighboring cells. In a conventional homogeneous network-i.e., a network based on macro cells only-fractional power control (FPC) is used to cope with intercell interference [1,2]. The impact of the FPC scheme on the signal-to-interference-plus-noise ratio (SINR) was evaluated in [3,4] in detail.…”