FAIR SHARING of CHANNEL RESOURCES in the COEXISTENCE of HETEROGENEOUS WIRELESS NETWORKS

Increasing spectrum resources in cellular networks are always needed to carry the exponential data traffic growth in wireless cellular networks. Limited spectrum resources in the licensed band have necessitated Long-Term Evolution (LTE) to explore available unlicensed spectrum where an incumbent WiFi system already exists. With the deployment of Licensed Assisted Access (LAA) that utilizes Listen Before Talk (LBT) for channel access in the unlicensed spectrum along with an incumbent WiFi, the coexistence of LAA and WiFi with acceptable fairness is a major challenge. In this work, we address the issues of licensed assisted access coexisting with incumbent WiFi in an unlicensed spectrum and provide solutions to dynamically tune system parameters of LAA stations to achieve maximum total throughput from the overall system taking into account fair allocation of throughput and airtime across different networks and stations. One major system parameter we study is the contention window size for back-off. Using the method of coupled Markov Chain, we show how an inherent trade-off between throughput and airtime fairness can be managed by adjusting the CW size of LAA. For single-channel, we show how coexistence with WiFi can be managed better with LAA-Cat3 than LAA-Cat4 when total throughput and fairness are to be taken into account. For multi-carrier sensing, we establish better coexistence by optimizing contention window sizes of each LAA station separately using an assignment technique based on a genetic algorithm. We extend our work into dual-carrier aggregation where some stations have the ability to combine two independent channels into a single aggregated channel to achieve higher performance. We show that in such a dual-carrier aggregation scenario, the distribution of stations (partition) over an individual and aggregated channel, and the system parameters (contention window size and load intensity) could be optimized to ensure fair allocation of resources without affecting the secondary channel too much

Soil resistivity influence due to the different utilization of electrical resistivity array

Electrical resistivity method (ERM) was increasingly adopted as an alternative tool in shallow subsurface exploration by the geotechnical engineers. This study presents the influence of soil electrical resistivity value (ERV) due to the different types of electrical resistivity array used in practice. The dissimilarity of ERV has always become a popular argument by engineers to the geophysicist due to its less fundamental knowledge of electrical resistivity method. From past experienced, the fundamental of ERM was less being exposed by the engineer thus creating several black boxes of the ERM basic theory which importantly required during the data acquisition and processing stages. Hence, the result produced from the ERM was difficult to deliver in a sound of definitive ways due to lack of knowledge and experienced of most engineers. Hence, this study presents the influence of soil ERV due to the different types of array used with particular reference to Wenner, Schlumberger, Dipole-dipole and Pole-dipole. A line of electrical resistivity imaging was performed on small embankment of lateritic soil in loose condition with different types of array using ABEM SAS (4000) equipment set. Three in line of soil samples were tested for moisture content (w) test immediately after the electrical resistivity data acquisition was completely measured. Moreover, particle size distribution test using dry and wet sieve was also being performed in order support to the ERV findings. It was found that the ERV was different for each types of array used even it was performed on the same particular location of the survey line. However, it was found that there is a consistent relationship between ERV and moisture content results which can be represent by ERV ∞ 1/w. Hence, it was found that ERV can be influenced by types of array used during the field measurement despite of the physical and chemical influences. Each types of array were applicable in subsurface profile investigation which normally subjected to the several considerations such as object target and the maximum depth of interest investigated

A survey of machine learning techniques applied to self organizing cellular networks

In this paper, a survey of the literature of the past fifteen years involving Machine Learning (ML) algorithms applied to self organizing cellular networks is performed. In order for future networks to overcome the current limitations and address the issues of current cellular systems, it is clear that more intelligence needs to be deployed, so that a fully autonomous and flexible network can be enabled. This paper focuses on the learning perspective of Self Organizing Networks (SON) solutions and provides, not only an overview of the most common ML techniques encountered in cellular networks, but also manages to classify each paper in terms of its learning solution, while also giving some examples. The authors also classify each paper in terms of its self-organizing use-case and discuss how each proposed solution performed. In addition, a comparison between the most commonly found ML algorithms in terms of certain SON metrics is performed and general guidelines on when to choose each ML algorithm for each SON function are proposed. Lastly, this work also provides future research directions and new paradigms that the use of more robust and intelligent algorithms, together with data gathered by operators, can bring to the cellular networks domain and fully enable the concept of SON in the near future

Integrated Data and Energy Communication Network: A Comprehensive Survey

OAPA In order to satisfy the power thirsty of communication devices in the imminent 5G era, wireless charging techniques have attracted much attention both from the academic and industrial communities. Although the inductive coupling and magnetic resonance based charging techniques are indeed capable of supplying energy in a wireless manner, they tend to restrict the freedom of movement. By contrast, RF signals are capable of supplying energy over distances, which are gradually inclining closer to our ultimate goal – charging anytime and anywhere. Furthermore, transmitters capable of emitting RF signals have been widely deployed, such as TV towers, cellular base stations and Wi-Fi access points. This communication infrastructure may indeed be employed also for wireless energy transfer (WET). Therefore, no extra investment in dedicated WET infrastructure is required. However, allowing RF signal based WET may impair the wireless information transfer (WIT) operating in the same spectrum. Hence, it is crucial to coordinate and balance WET and WIT for simultaneous wireless information and power transfer (SWIPT), which evolves to Integrated Data and Energy communication Networks (IDENs). To this end, a ubiquitous IDEN architecture is introduced by summarising its natural heterogeneity and by synthesising a diverse range of integrated WET and WIT scenarios. Then the inherent relationship between WET and WIT is revealed from an information theoretical perspective, which is followed by the critical appraisal of the hardware enabling techniques extracting energy from RF signals. Furthermore, the transceiver design, resource allocation and user scheduling as well as networking aspects are elaborated on. In a nutshell, this treatise can be used as a handbook for researchers and engineers, who are interested in enriching their knowledge base of IDENs and in putting this vision into practice

On the superiority of improper Gaussian signaling in wireless interference MIMO scenarios

©2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Recent results have elucidated the benefits of using improper Gaussian signaling (IGS) as compared to conventional proper Gaussian signaling (PGS) in terms of achievable rate for interference-limited conditions. This paper exploits majorization theory tools to formally quantify the gains of IGS along with widely linear transceivers for MIMO systems in interferencelimited scenarios. The MIMO point-to-point channel with interference (P2P-I) is analyzed, assuming that received interference can be either proper or improper, and we demonstrate that the use of the optimal IGS when received interference is improper strictly outperforms (in terms of achievable rate and mean square error) the use of the optimal PGS when interference is proper. Then, these results are extended to two practical situations. First, the MIMO Z-interference channel (Z-IC) is investigated, where a trade-off arises: with IGS we could increase the achievable rate of the interfered user while gracefully degrading the rate of the non-interfered user. Second, these concepts are applied to a two-tier heterogeneous cellular network (HCN) where macrocells and smallcells coexist and multiple MIMO Z-IC appear.Peer ReviewedPostprint (author's final draft