Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userMachine Learning-based Inter-Beam Inter-Cell Interference Mitigation in mmWave
99
0
0.0
(
0
)
Added by
Medhat Elsayed
Publication date
2021
fields
Informatics Engineering
and research's language is
English
Ask ChatGPT about the research
No Arabic abstract
In this paper, we address inter-beam inter-cell interference mitigation in 5G networks that employ millimeter-wave (mmWave), beamforming and non-orthogonal multiple access (NOMA) techniques. Those techniques play a key role in improving network capacity and spectral efficiency by multiplexing users on both spatial and power domains. In addition, the coverage area of multiple beams from different cells can intersect, allowing more flexibility in user-cell association. However, the intersection of coverage areas also implies increased inter-beam inter-cell interference, i.e. interference among beams formed by nearby cells. Therefore, joint user-cell association and inter-beam power allocation stand as a promising solution to mitigate inter-beam, inter-cell interference. In this paper, we consider a 5G mmWave network and propose a reinforcement learning algorithm to perform joint user-cell association and inter-beam power allocation to maximize the sum rate of the network. The proposed algorithm is compared to a uniform power allocation that equally divides power among beams per cell. Simulation results present a performance enhancement of 13-30% in networks sum-rate corresponding to the lowest and highest traffic loads, respectively.
rate research
Read More
In this paper, for the first time, we analytically prove that the uplink (UL) inter-cell interference in frequency division multiple access (FDMA) small cell networks (SCNs) can be well approximated by a lognormal distribution under a certain condition. The lognormal approximation is vital because it allows tractable network performance analysis with closed-form expressions. The derived condition, under which the lognormal approximation applies, does not pose particular requirements on the shapes/sizes of user equipment (UE) distribution areas as in previous works. Instead, our results show that if a path loss related random variable (RV) associated with the UE distribution area, has a low ratio of the 3rd absolute moment to the variance, the lognormal approximation will hold. Analytical and simulation results show that the derived condition can be readily satisfied in future dense/ultra-dense SCNs, indicating that our conclusions are very useful for network performance analysis of the 5th generation (5G) systems with more general cell deployment beyond the widely used Poisson deployment.
Low Earth orbit (LEO) satellite constellations rely on inter-satellite links (ISLs) to provide global connectivity. However, one significant challenge is to establish and maintain inter-plane ISLs, which support communication between different orbital planes. This is due to the fast movement of the infrastructure and to the limited computation and communication capabilities on the satellites. In this paper, we make use of antenna arrays with either Butler matrix beam switching networks or digital beam steering to establish the inter-plane ISLs in a LEO satellite constellation. Furthermore, we present a greedy matching algorithm to establish inter-plane ISLs with the objective of maximizing the sum of rates. This is achieved by sequentially selecting the pairs, switching or pointing the beams and, finally, setting the data rates. Our results show that, by selecting an update period of 30 seconds for the matching, reliable communication can be achieved throughout the constellation, where the impact of interference in the rates is less than 0.7 % when compared to orthogonal links, even for relatively small antenna arrays. Furthermore, doubling the number of antenna elements increases the rates by around one order of magnitude.
Appearing on the stage quite recently, the Low Power Wide Area Networks (LPWANs) are currently getting much of attention. In the current paper we study the susceptibility of one LPWAN technology, namely LoRaWAN, to the inter-network interferences. By means of excessive empirical measurements employing the certified commercial transceivers, we characterize the effect of modulation coding schemes (known for LoRaWAN as data rates (DRs)) of a transmitter and an interferer on probability of successful packet delivery while operating in EU 868 MHz band. We show that in reality the transmissions with different DRs in the same frequency channel can negatively affect each other and that the high DRs are influenced by interferences more severely than the low ones. Also, we show that the LoRa-modulated DRs are affected by the interferences much less than the FSK-modulated one. Importantly, the presented results provide insight into the network-level operation of the LoRa LPWAN technology in general, and its scalability potential in particular. The results can also be used as a reference for simulations and analyses or for defining the communication parameters for real-life applications.
In molecular communication via diffusion (MCvD), the inter-symbol interference (ISI) is a well known severe problem that deteriorates both data rates and link reliability. ISI mainly occurs due to the slow and highly random propagation of the messenger molecules, which causes the emitted molecules from the previous symbols to interfere with molecules from the current symbol. An effective way to mitigate the ISI is using enzymes to degrade undesired molecules. Prior work on ISI mitigation by enzymes has assumed an infinite amount of enzymes randomly distributed around the molecular channel. Taking a different approach, this paper assumes an MCvD channel with a limited amount of enzymes. The main question this paper addresses is how to deploy these enzymes in an effective structure so that ISI mitigation is maximized. To find an effective MCvD channel environment, this study considers optimization of the shape of the transmitter node, the deployment location and structure, the size of the enzyme deployed area, and the half-lives of the enzymes. It also analyzes the dependence of the optimum size of the enzyme area on the distance and half-life.
In this document, we are primarily interested in computing the probabilities of various types of dependencies that can occur in a multi-cell infrastructure network.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
