Cellular Fronthauling for Data Capacity Increase in Underserved Spaces

The increase in wireless data traffic continues and is a product of several factors. First, new technologies and capabilities enable new use cases for which new products emerge. Then, with the growing user adoption over time, the data traffic is further increased. As a result, the actual growth numbers vary year over year, but the trend is sustained. People nowadays also expect ubiquitous availability of mobile connectivity and use cloud services or stream music and video. Moreover, an increasing number of machines are being connected too. While mobile network operators (MNOs) deploy outdoor cellular networks, a significant portion of the mobile data traffic is consumed or originates indoors or while traveling in trains. To this end, MNOs constantly upgrade their networks to satisfy the capacity demand. Additionally, new and wider frequency bands are made available by regulators. However, the mid-band frequencies between 3 GHz and 6 GHz poorly enter buildings, and outdoor cells on millimeter-wave (mmWave) frequencies (24 GHz to 100 GHz) are practically unusable indoors and inside modern railways with their metallic hull and coated windows acting as Faraday cages. The increasing network densification with local cell sites (also inside shielded structures) can provide a partial solution. However, the required fiber and roll-out process is very costly and takes time. Moreover, providing sufficient capacity for the increasing data traffic demand inside buildings and trains is difficult where an optical fiber backhaul is too costly or impossible.State-of-the-art solutions are analyzed for solving the indoor capacity challenge. However, we found that these rely on or impact the existing outdoor cellular network and thus cannot provide additional capacity to the network that is used indoors. As a solution, we propose the mmWave bridge, an amplify-and-forward out-of-band repeater concept. It is a radio access technology (RAT) transparent and cost-efficient method to fronthaul mobile cells. Moreover, it provides wireless data capacity inside buildings, vehicles, or concealed areas outdoors, where low signal levels drastically limit the achievable capacity or prevent communication with distant base stations. The cellular signal of a base station is fronthauled over newly available mmWave frequencies outdoor without interfering with the existing cellular network. Mid-band frequencies are used indoors to provide sufficient coverage beyond rooms and, at the same time, benefit from the outdoor-to-indoor attenuation reducing possible interference.The benefits of the mmWave bridge are described, and we discuss the corresponding challenges and solutions. Moreover, a hardware prototype was developed based on commercial off-the-shelf components. We have tested our prototype in three use cases to demonstrate the functionality and compatibility with commercial infrastructure and mobile terminals and present the measurement results. We can show that the entire capacity of a mobile cell can be fronthauled over distances in relation to the mmWave frequency propagation and signal power. Finally, the amplify-and-forward out-of-band repeater concept is generalized regarding the fronthaul carrier frequency. The use of beamforming antennas on RAT-transparent repeaters without access to in-band beam control is investigated, and a solution with a minimal impact of a few percent in throughput reduction is presented.

Beam Selection and Tracking for Amplify-and-Forward Repeaters

Andreas Peter Burg, Ruben Merz, Adrian Schumacher

Mobile network operators constantly have to upgrade their cellular network to satisfy the public's hunger for increasing data capacity. However, regulatory limits regarding allowed electromagnetic field strength on existing cell sites often limit or prevent the installation of new cells on additional frequency bands. Further densifying the radio access infrastructure by means of new cell sites takes time because of the site acquisition, the need for permissions, and the civil construction. To this end, amplify-and-forward repeaters are a cost-efficient method to provide mobile wireless data capacity to concealed areas outdoors, inside buildings, or vehicles, where low signal levels drastically limit the achievable capacity or even prevent communication with distant base stations. Repeaters with high-gain beamforming antennas can be used to decrease the path loss and thereby offer a higher capacity than user equipment otherwise could achieve. Since those highly directional beams must be constantly adjusted, we propose methods to align and track the beam even without having access to in-band beam control mechanisms. Numerical analyses with measurement data show that such non-invasive (system data-agnostic) methods are feasible and only incur a few percent in throughput reduction.

IEEE2022

Fundamental limits and optimal operation in large wireless networks

Ayfer Özgür Aydin

Wireless adhoc networks consist of users that want to communicate with each other over a shared wireless medium. The users have transmitting and receiving capabilities but there is no additional infrastructure for assisting communication. This is in contrast to existing wireless systems, cellular networks for example, where communication between wireless users heavily relies on an additional infrastructure of base stations connected with a high-capacity wired backbone. The fact that they are infrastructureless makes wireless adhoc networks inexpensive, easy to build and robust but at the same time technically more challenging. The fundamental challenge is how to deal with interference: many simultaneous transmissions have to be accommodated on the same wireless channel when each of these transmissions constitutes interference for the others, degrading the quality of the communication. The traditional approach to wireless adhoc networks is to organize users so that they relay information for each other in a multi-hop fashion. Such multi-hopping strategies face scalability problems at large system size. As shown by Gupta and Kumar in their seminal work in 2000, the maximal communication rate per user under such strategies scales inversely proportional to the square root of the number of users in the network, hence decreases to zero with increasing system size. This limitation is due to interference that precludes having many simultaneous point-to-point transmissions inside the network. In this thesis, we propose a multiscale hierarchical cooperation architecture for distributed MIMO communication in wireless adhoc networks. This novel architecture removes the interference limitation at least as far as scaling is concerned: we show that the per-user communication rate under this strategy does not degrade significantly even if there are more and more users entering into the network. This is in sharp contrast to the performance achieved by the classical multi-hopping schemes. However, the overall picture is much richer than what can be depicted by a single scheme or a single scaling law formula. Nowadays, wireless adhoc networks are considered for a wide range of practical applications and this translates to having a number of system parameters (e.g., area, power, bandwidth) with large operational range. Different applications lie in different parameter ranges and can therefore exhibit different characteristics. A thorough understanding of wireless adhoc networks can only be obtained by exploring the whole parameter space. Existing scaling law formulations are insufficient for this purpose as they concentrate on very small subsets of the system parameters. We propose a new scaling law formulation for wireless adhoc networks that serves as a mathematical tool to characterize their fundamental operating regimes. For the standard wireless channel model where signals are subject to power path-loss attenuation and random phase changes, we identify four qualitatively different operating regimes in wireless adhoc networks with large number of users. In each of these regimes, we characterize the dependence of the capacity on major system parameters. In particular, we clarify the impact of the power and bandwidth limitations on performance. This is done by deriving upper bounds on the information theoretic capacity of wireless adhoc networks in Chapter 3, and constructing communication schemes that achieve these upper bounds in Chapter 4. Our analysis identifies three engineering quantities that together determine the operating regime of a given wireless network: the short-distance signal-to-noise power ratio (SNRs), the long-distance signal-to-noise power ratio (SNRl) and the power path-loss exponent of the environment. The right communication strategy for a given application is dictated by its operating regime. We show that conventional multi-hopping schemes are optimal when the power path-loss exponent of the environment is larger than 3 and SNRs ≪ 0 dB. Such networks are extremely power-limited. On the other hand, the novel architecture proposed in this thesis, based on hierarchical cooperation and distributed MIMO, is the fundamentally right strategy for wireless networks with SNRl ≫ 0 dB. Such networks experience no power limitation. In the intermediate cases, captured by the remaining two operating regimes, neither multi-hopping nor hierarchical-MIMO achieves optimal performance. We construct new schemes for these regimes that achieve capacity. The proposed characterization of wireless adhoc networks in terms of their fundamental operating regimes, is analogous to the familiar understanding of the two operating regimes of the point-to-point additive white Gaussian noise (AWGN) channel. From an engineering point of view, one of the most important contributions of Shannon's celebrated capacity formula is to identify two qualitatively different operating regimes on this channel. Determined by its signal-to-noise power ratio (SNR), an AWGN channel can be either in a bandwidth-limited (SNR ≫ 0 dB) or a power-limited (SNR ≪ 0 dB) regime. Communication system design for this channel has been primarily driven by the operating regime one is in.

EPFL2009

Routing and search on large scale networks

Dominique Florian Tschopp

In this thesis, we address two seemingly unrelated problems, namely routing in large wireless ad hoc networks and comparison based search in image databases. However, the underlying problem is in essence similar and we can use the same strategy to attack those two problems. In both cases, the intrinsic complexity of the problem is in some sense low, and we can exploit this fact to design efficient algorithms. A wireless ad hoc network is a communication network consisting of wireless devices such as for instance laptops or cell phones. The network does not have any fixed infrastructure, and hence nodes which cannot communicate directly over the wireless medium must use intermediate nodes as relays. This immediately raises the question of how to select the relay nodes. Ideally, one would like to find a path from the source to the destination which is as short as possible. The length of the found path, also called route, typically depends on how much signaling traffic is generated in order to establish the route. This is the fundamental trade-off that we will investigate in this thesis. As mentioned above, we try and exploit the fact that the communication network is intrinsically low-dimensional, or in other words has low complexity. We show that this is indeed the case for a large class of models and that we can design efficient algorithms for routing that use this property. Low dimensionality implies that we can well embed the network in a low-dimensional space, or build simple hierarchical decompositions of the network. We use both those techniques to design routing algorithms. Comparison based search in image databases is a new problem that can be defined as follows. Given a large database of images, can a human user retrieve an image which he has in mind, or at least an image similar to that image, without going sequentially through all images? More precisely, we ask whether we can search a database of images only by making comparisons between images. As a case in point, we ask whether we can find a query image q only by asking questions of the type "does image q look more like image A or image B"? The analogous to signaling traffic for wireless networks would here be the questions we can ask human users in a learning phase anterior to the search. In other words, we would like to ask as few questions as possible to pre-process and prepare the database, while guaranteeing a certain quality of the results obtained in the search phase. As the underlying image space is not necessarily metric, this raises new questions on how to search spaces for which only rank information can be obtained. The rank of A with respect to B is k, if A is B's kth nearest neighbor. In this setup, low-dimensionality is analogous to the homogeneity of the image space. As we will see, the homogeneity can be captured by properties of the rank relationships. In turn, homogeneous spaces can be well decomposed hierarchically using comparisons. Further, it allows us to design good hash functions. To design efficient algorithms for these two problems, we can apply the same techniques mutatis mutandis. In both cases, we relied on the intuition that the problem has a low intrinsic complexity, and that we can exploit this fact. Our results come in the form of simulation results and asymptotic bounds.