We explore the effect of dimensionality on the nearest neighbor problem. We show that under a broad set of conditions (much broader than independent and identically distributed dimensions), as dimensionality increases, the distance to the nearest data point approaches the distance to the farthest data point. To provide a practical perspective, we present empirical results on both real and synthetic data sets that demonstrate that this effect can occur for as few as 10-15 dimensions. These results should not be interpreted to mean that high-dimensional indexing is never meaningful; we illustrate this point by identifying some high-dimensional workloads for which this effect does not occur. However, our results do emphasize that the methodology used almost universally in the database literature to evaluate high-dimensional indexing techniques is flawed, and should be modified. In particular, most such techniques proposed in the literature are not evaluated versus simple linear scan, and are evaluated over workloads for which nearest neighbor is not meaningful. Often, even the reported experiments, when analyzed carefully, show that linear scan would outperform the techniques being proposed on the workloads studied in high (10-15) dimensionality!.

When is nearest neighbor meaningful

The adoption of a reconfigurable intelligent surface (RIS) for downlink multi-user communication from a multi-antenna base station is investigated in this paper. We develop energy-efficient designs for both the transmit power allocation and the phase shifts of the surface reflecting elements subject to individual link budget guarantees for the mobile users. This leads to non-convex design optimization problems for which to tackle we propose two computationally affordable approaches, capitalizing on alternating maximization, gradient descent search, and sequential fractional programming. Specifically, one algorithm employs gradient descent for obtaining the RIS phase coefficients, and fractional programming for optimal transmit power allocation. Instead, the second algorithm employs sequential fractional programming for the optimization of the RIS phase shifts. In addition, a realistic power consumption model for RIS-based systems is presented, and the performance of the proposed methods is analyzed in a realistic outdoor environment. In particular, our results show that the proposed RIS-based resource allocation methods are able to provide up to 300% higher energy efficiency in comparison with the use of regular multi-antenna amplify-and-forward relaying.

Reconfigurable Intelligent Surfaces for Energy Efficiency in Wireless Communication

The adoption of a Reconfigurable Intelligent Surface (RIS) for downlink multi-user communication from a multi-antenna base station is investigated in this paper. We develop energy-efficient designs for both the transmit power allocation and the phase shifts of the surface reflecting elements, subject to individual link budget guarantees for the mobile users. This leads to non-convex design optimization problems for which to tackle we propose two computationally affordable approaches, capitalizing on alternating maximization, gradient descent search, and sequential fractional programming. Specifically, one algorithm employs gradient descent for obtaining the RIS phase coefficients, and fractional programming for optimal transmit power allocation. Instead, the second algorithm employs sequential fractional programming for the optimization of the RIS phase shifts. In addition, a realistic power consumption model for RIS-based systems is presented, and the performance of the proposed methods is analyzed in a realistic outdoor environment. In particular, our results show that the proposed RIS-based resource allocation methods are able to provide up to $300\%$ higher energy efficiency, in comparison with the use of regular multi-antenna amplify-and-forward relaying.

Space-air-ground integrated network (SAGIN), as an integration of satellite systems, aerial networks, and terrestrial communications, has been becoming an emerging architecture and attracted intensive research interest during the past years. Besides bringing significant benefits for various practical services and applications, SAGIN is also facing many unprecedented challenges due to its specific characteristics, such as heterogeneity, self-organization, and time-variability. Compared to traditional ground or satellite networks, SAGIN is affected by the limited and unbalanced network resources in all three network segments, so that it is difficult to obtain the best performances for traffic delivery. Therefore, the system integration, protocol optimization, resource management, and allocation in SAGIN is of great significance. To the best of our knowledge, we are the first to present the state-of-the-art of the SAGIN since existing survey papers focused on either only one single network segment in space or air, or the integration of space-ground, neglecting the integration of all the three network segments. In light of this, we present in this paper a comprehensive review of recent research works concerning SAGIN from network design and resource allocation to performance analysis and optimization. After discussing several existing network architectures, we also point out some technology challenges and future directions.

Space-Air-Ground Integrated Network: A Survey

Interest in Wireless Body Area Networks (WBANs) has increased significantly in recent years thanks to the advances in microelectronics and wireless communications. Owing to the very stringent application requirements in terms of reliability, energy efficiency, and low device complexity, the design of these networks requires the definition of new protocols with respect to those used in general purpose wireless sensor networks. This motivates the effort in research activities and in standardisation process of the last years. This survey paper aims at reporting an overview of WBAN main applications, technologies and standards, issues in WBANs design, and evolutions. Some case studies are reported, based on both real implementation and experimentation on the field, and on simulations. These results have the aim of providing useful insights for WBAN designers and of highlighting the main issues affecting the performance of these kind of networks.

A Survey on Wireless Body Area Networks: Technologies and Design Challenges

Modern cellular networks in traditional frequency bands are notoriously interference-limited, especially in urban areas, where base stations are deployed in close proximity to one another. The latest releases of LTE incorporate features for coordinating downlink transmissions as an efficient means of managing interference. Recent field trial results and theoretical studies of the performance of JT CoMP schemes revealed, however, that their gains are not as high as initially expected, despite the large coordination overhead. These schemes are known to be very sensitive to defects in synchronization or information exchange between coordinating base stations as well as uncoordinated interference. In this article, we review recent advanced CB schemes as alternatives, requiring less overhead than JT CoMP while achieving good performance in realistic conditions. By stipulating that in certain LTE scenarios of increasing interest, uncoordinated interference constitutes a major factor in the performance of CoMP techniques at large, we hereby assess the resilience of the stateof- the-art CB to uncoordinated interference. We also describe how these techniques can leverage the latest specifications of current cellular networks, and how they may perform when we consider standardized feedback and coordination. This allows us to identify some key road blocks and research directions to address as LTE evolves toward the future of mobile communications.

Advanced coordinated beamforming for the downlink of future LTE cellular networks

As 4G wireless networks are vastly and rapidly deployed worldwide, 5G with its advanced vision of all connected world and zero distance communications is already at the corner. Along with the super quality of user experience brought by these new networks, the shockingly increasing energy consumption of wireless networks has become a worrying economic issue for operators and a big challenge for sustainable development. Green Transmission Technologies (GTT) is a project focusing on the energy-efficient design of physical-layer transmission technologies and MAC-layer radio resource management in wireless networks. In particular, fundamental tradeoffs between spectrum efficiency and energy efficiency have been identified and explored for energy-efficiency-oriented design and optimization. In this article, four selected GTT solutions are introduced, focusing on how they utilize the degrees of freedom in different resource domains, as well as how they balance the tradeoff between energy and spectrum efficiency. On top of the elaboration of separated solutions, the GTT toolbox is introduced as a systematic tool and unified simulation platform to integrate the proposed GTT solutions together.

https://ir.nctu.edu.tw:443/bitstream/11536/124135/1/000346036400016.pdf

Green Transmission Technologies for Balancing the Energy Efficiency and Spectrum Efficiency Trade-off

We report on experimental results on the use of a learning-based approach to infer the location of a mobile user of a cellular network within a cell, for a 5G-type Massive multiple input, multiple output (MIMO) system. We describe how the sample spatial covariance matrix computed from the CSI can be used as the input to a learning algorithm which attempts to relate it to user location. We discuss several learning approaches, and analyze in depth the application of extreme learning machines, for which theoretical approximate performance benchmarks are available, to the localization problem. We validate the proposed approach using experimental data collected on a Huawei 5G testbed, provide some performance and robustness benchmarks, and discuss practical issues related to the deployment of such a technique in 5G networks.

CSI-based Outdoor Localization for Massive MIMO: Experiments with a Learning Approach

With the advent of 5G, standardization and research are currently defining the next generation of radio access. Considering the high constraints imposed by future standards, disruptive technologies such as massive MIMO are being proposed. At the heart of this process are wireless channel models that now need to cover a massive increase in design parameters, a large variety of frequency bands, and heterogeneous deployments. This tutorial presents the key drivers behind the evolution of channel modeling and simulation tools as a platform to evaluate future radio access technologies. This evolution comes with new challenges for the research community; this tutorial surveys these challenges, and the approaces to overcome them.

Trends and challenges in wireless channel modeling for evolving radio access

Body area networks (BAN) offer amazing perspectives to instrument and support humans in many aspects of their life. Among all possible applications, this paper focuses on body monitoring applications having a body equipped with a set of sensors transmitting in real time their measures to a common sink. In this context, at the application level, the network fits with a star topology, which is quite usual in the broad scope of wireless networks. Unfortunately, the structure of the network at the physical layer is totally different. Indeed, due to the specificity of BAN radio channel features, all radio links are not stationary and all sensors suffer from link losses during independent time frames. In wireless networks, link losses are often coped with multi-hop transmission schemes to ensure a good connectivity. However, since the radio links are not stationary, the multi-hop routes should adapt quickly to BAN changes. We instead propose in this work a different approach based on opportunistic relaying. The concept relies on electing some sensors to support the transmission of other ones having a worst connection. Instead of changing the relay time to time, we rather select a relay node from a statistical perspective. We evaluate this approach from a theoretical point of view and on realistic simulations using the packet error rate outage probability as a performance criterion.

Paul Ferrand

Papers

Advanced coordinated beamforming for the downlink of future LTE cellular networks

Green Transmission Technologies for Balancing the Energy Efficiency and Spectrum Efficiency Trade-off

CSI-based Outdoor Localization for Massive MIMO: Experiments with a Learning Approach

Trends and challenges in wireless channel modeling for evolving radio access

Performance evaluation of direct and cooperative transmissions in body area networks