Scalability study of backhaul capacity sensitive network selection scheme in LTE-wifi HetNet

Wireless Heterogeneous Network (HetNet) with small cells presents a new backhauling challenge which differs from those of experienced by conventional macro-cells. In practice, the choice of backhaul technology for these small cells whether fiber, xDSL, point–to-point and point-to-multipoint wireless, or multi-hop/mesh networks, is often governed by availability and cost, and not by required capacity. Therefore, the resulting backhaul capacity of the small cells in HetNet is likely to be non-uniform due to the mixture of backhaul technologies adopted. In such an environment, a question then arises whether a network selection strategy that considers the small cells’ backhaul capacity will improve the end users’ usage experience. In this paper, a novel Dynamic Backhaul Capacity Sensitive (DyBaCS) network selection schemes (NSS) is proposed and compared with two commonly used network NSSs, namely WiFi First (WF) and Physical Data Rate (PDR) in an LTE-WiFi HetNet environment. The proposed scheme is evaluated in terms of average connection or user throughput1and fairness among users. The effects of varying WiFi backhaul capacity (uniform and non-uniform distribution), WiFi-LTE coverage ratio, user density and WiFi access points (APs) density within the HetNet form the focus of this paper. Results show that the DyBaCS scheme generally provides superior fairness and user throughput performance across the range of backhaul capacity considered. Besides, DyBaCS is able to scale much better than WF and PDR across different user and WiFi densities

Advanced Technologies Enabling Unlicensed Spectrum Utilization in Cellular Networks

As the rapid progress and pleasant experience of Internet-based services, there is an increasing demand for high data rate in wireless communications systems. Unlicensed spectrum utilization in Long Term Evolution (LTE) networks is a promising technique to meet the massive traffic demand. There are two effective methods to use unlicensed bands for delivering LTE traffic. One is offloading LTE traffic toWi-Fi. An alternative method is LTE-unlicensed (LTE-U), which aims to directly use LTE protocols and infrastructures over the unlicensed spectrum. It has also been pointed out that addressing the above two methods simultaneously could further improve the system performance. However, how to avoid severe performance degradation of the Wi-Fi network is a challenging issue of utilizing unlicensed spectrum in LTE networks. Specifically, first, the inter-system spectrum sharing, or, more specifically, the coexistence of LTE andWi-Fi in the same unlicensed spectrum is the major challenge of implementing LTE-U. Second, to use the LTE and Wi-Fi integration approach, mobile operators have to manage two disparate networks in licensed and unlicensed spectrum. Third, optimization for joint data offloading to Wi-Fi and LTE-U in multi- cell scenarios poses more challenges because inter-cell interference must be addressed. This thesis focuses on solving problems related to these challenges. First, the effect of bursty traffic in an LTE and Wi-Fi aggregation (LWA)-enabled network has been investigated. To enhance resource efficiency, the Wi-Fi access point (AP) is designed to operate in both the native mode and the LWA mode simultaneously. Specifically, the LWA-modeWi-Fi AP cooperates with the LTE base station (BS) to transmit bearers to the LWA user, which aggregates packets from both LTE and Wi-Fi. The native-mode Wi-Fi AP transmits Wi-Fi packets to those native Wi-Fi users that are not with LWA capability. This thesis proposes a priority-based Wi-Fi transmission scheme with congestion control and studied the throughput of the native Wi-Fi network, as well as the LWA user delay when the native Wi-Fi user is under heavy traffic conditions. The results provide fundamental insights in the throughput and delay behavior of the considered network. Second, the above work has been extended to larger topologies. A stochastic geometry model has been used to model and analyze the performance of an MPTCP Proxy-based LWA network with intra-tier and cross-tier dependence. Under the considered network model and the activation conditions of LWA-mode Wi-Fi, this thesis has obtained three approximations for the density of active LWA-mode Wi-Fi APs through different approaches. Tractable analysis is provided for the downlink (DL) performance evaluation of large-scale LWA networks. The impact of different parameters on the network performance have been analyzed, validating the significant gain of using LWA in terms of boosted data rate and improved spectrum reuse. Third, this thesis also takes a significant step of analyzing joint multi-cell LTE-U and Wi-Fi network, while taking into account different LTE-U and Wi-Fi inter-working schemes. In particular, two technologies enabling data offloading from LTE to Wi-Fi are considered, including LWA and Wi-Fi offloading in the context of the power gain-based user offloading scheme. The LTE cells in this work are subject to load-coupling due to inter-cell interference. New system frameworks for maximizing the demand scaling factor for all users in both Wi-Fi and multi-cell LTE networks have been proposed. The potential of networks is explored in achieving optimal capacity with arbitrary topologies, accounting for both resource limits and inter-cell interference. Theoretical analyses have been proposed for the proposed optimization problems, resulting in algorithms that achieve global optimality. Numerical results show the algorithms’ effectiveness and benefits of joint use of data offloading and the direct use of LTE over the unlicensed band. All the derived results in this thesis have been validated by Monte Carlo simulations in Matlab, and the conclusions observed from the results can provide guidelines for the future unlicensed spectrum utilization in LTE networks

Location-Enabled IoT (LE-IoT): A Survey of Positioning Techniques, Error Sources, and Mitigation

The Internet of Things (IoT) has started to empower the future of many industrial and mass-market applications. Localization techniques are becoming key to add location context to IoT data without human perception and intervention. Meanwhile, the newly-emerged Low-Power Wide-Area Network (LPWAN) technologies have advantages such as long-range, low power consumption, low cost, massive connections, and the capability for communication in both indoor and outdoor areas. These features make LPWAN signals strong candidates for mass-market localization applications. However, there are various error sources that have limited localization performance by using such IoT signals. This paper reviews the IoT localization system through the following sequence: IoT localization system review -- localization data sources -- localization algorithms -- localization error sources and mitigation -- localization performance evaluation. Compared to the related surveys, this paper has a more comprehensive and state-of-the-art review on IoT localization methods, an original review on IoT localization error sources and mitigation, an original review on IoT localization performance evaluation, and a more comprehensive review of IoT localization applications, opportunities, and challenges. Thus, this survey provides comprehensive guidance for peers who are interested in enabling localization ability in the existing IoT systems, using IoT systems for localization, or integrating IoT signals with the existing localization sensors

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

60 GHz Wireless Propagation Channels: Characterization, Modeling and Evaluation

To be able to connect wirelessly to the internet is nowadays a part of everyday life and the number of wireless devices accessing wireless networks worldwide are increasing rapidly. However, with the increasing number of wireless devices and applications and the amount available bandwidth, spectrum shortage is an issue. A promising way to increase the amount of available spectrum is to utilize frequency bands in the mm-wave range of 30-300 GHz that previously have not been used for typical consumer applications. The 60 GHz band has been pointed out as a good candidate for short range, high data rate communications, as the amount of available bandwidth is at least 5 GHz worldwide, with most countries having 7 GHz of bandwidth available in this band. This large bandwidth is expected to allow for wireless communication with bit rates up to 7 Gbit/s, which can be compared to the typical WLAN systems of today that typically provide bit rates up to 0.6 Gbit/s. However, the performance of any wireless system is highly dependent on the properties and characteristics of the wireless propagation channel. This thesis focuses on indoor short range wireless propagation channels in the 60 GHz band and contains a collection of papers that characterizes, models and evaluates different aspects that are directly related to the propagation channel properties. Paper I investigates the directional properties of the indoor 60 GHz wireless radio channel based on a set of indoor measurements in a conference room. In the paper, the signal pathways and propagation mechanisms for the strongest paths are identified. The results show that first and second order interactions account for the major contribution of the received power. The results also show that finer structures, such as ceiling lamps, can be significant interacting objects. Paper II presents a cluster-based double-directional channel model for 60 GHz indoor multiple-input multiple-output (MIMO) systems. This paper is a direct continuation of the results in paper I. The model supports arbitrary antenna elements and array configurations and is validated against measurement data. The validation shows that the channel model is able to efficiently reproduce the statistical properties of the measured channels. The presented channel model is also compared with the 60 GHz channel models developed for the industry standards IEEE802.15.3c and IEEE802.11ad. Paper III characterizes the effect of shadowing due to humans and other objects. Measurements of the shadowing gain for human legs, metallic sheets, as well as metallic and plastic cylinders are presented. It is shown that the shadowing gain of these objects are fairly similar and that the shadowing due to the metal cylinder can be determined based on the geometrical theory of diffraction. Next, the shadowing due to a water-filled human body phantom is compared with the shadowing due to real humans. The results show that the water-filled phantom has shadowing properties similar to those of humans and is therefore suitable for use in 60 GHz human body shadowing measurements. Paper IV presents a novel way of estimating the cluster decay and fading. Previously, the cluster decay has usually been determined by performing a simple linear regression, without considering the effects of the noise floor and cluster fading. The paper presents an estimation method which takes these effects into account and jointly estimates both the cluster decay and cluster fading. It is shown that this estimation method can greatly improve the estimated parameters. Paper V evaluates the capacity improvement capability of spatial multiplexing and beamforming techniques for 60 GHz systems in an indoor environment. In this paper, beamforming refers to conventional gain focusing in the direction of the strongest propagation path. The paper uses a capacity metric that only depends on the multi-path richness of the propagation channel and the antenna aperture size. In the paper, it is shown that, when the link budget is limited due to electrically small antennas and long Tx-Rx separation distances, beamforming approximates the capacity of spatial multiplexing. However, spatial multiplexing is a worthwhile option when Rx SNR is favorable and a higher peak data rate is required. Paper VI describes different methods for the clustering of wireless multi-path components. In the literature, the clustering method that is predominantly used is the K-means algorithm, or a power-weighted version of K-means, called K-power means. In this paper, we point out that K-means is a special case of a Gaussian mixture model (GMM). The paper presents a clustering method based on a GMM. This method is able to handle arbitrary cluster spreads in the different dimensions better than the K-means algorithm. A power-weighted version of the GMM is also presented. In addition to this, a mixture model based on asymmetric Laplace distributions is also presented, with and without power-weighting. Paper VII is based on channel measurements in a small and a large room, where the Tx and Rx arrays have dual polarized elements. Using these measurements, the cross-polarization ratio (XPR) of the multi-path components are characterized. This gives valuable information on how the MPCs are affected by the propagation channel. A statistical description of the XPR is also needed for the development of a propagation channel model that supports polarization. The paper also investigates the eigenvalue spreads for single and dual polarized elements. Furthermore, the measurements include LOS and NLOS measurement, where the NLOS scenarios include water-filled human presented in paper III. The results show that the capacity can be greatly improved if dual-polarized elements are used, and that the XPR values are in general higher compared to lower frequencies