Alessandro Chiumento

LTE in the sky: trading off propagation benefits with interference costs for aerial nodes

The popularity of unmanned aerial vehicles has exploded over the last few years, urgently demanding solutions to transfer large amounts of data from the UAV to the ground. Conversely, a control channel to the UAV is desired, in order to safely operate these vehicles remotely. This article analyzes the use of LTE for realizing this downlink data and uplink control. By means of measurements and simulations, we study the impact of interference and path loss when transmitting data to and from the UAV. Two scenarios are considered in which UAVs act as either base stations transmitting in downlink or UEs transmitting in uplink, and their impact on the respective downlink and uplink performance of an LTE ground network is analyzed. Both measurements and simulations are used to quantify such impact for a range of scenarios with varying altitude, distance from the base station, or UAV density. The measurement sets show that signal-to-interference ratio decreases up to 7 dB for UAVs at 150 m compared to ground users. Simulation results show that a UAV density of 10/km2 gives an average degradation of the signal-to-interference ratio of more than 6 dB. It is concluded that interference is going to be a major limiting factor when LTE enabled UAVs are introduced, and that strong technical solutions will have to be found.

Analysis of power efficiency of schedulers in LTE

In this work we analyse the behaviour of six different LTE scheduling algorithms, namely the round robin, best CQI, proportional fair, Max-Min, resource fair and the iterative hungarian schedulers. A downlink LTE network is simulated and the properties of the schedulers are analysed for a varying number of served users. These schedulers are studied from a throughput and fairness perspective through system level simulations. Furthermore the impact of each scheduler on the energy consumption is also computed with the aid of a flexible base station power model. The simulations show that the best CQI scheduler proves to deliver the highest data rate but lowest fairness while the Max-Min achieves exactly the opposite. The round robin delivers the worst overall performances while the other ones behave similarly in between. This work argues for the introduction of an energy consumption figure of merit for a fair and insightful comparison between specific scheduling algorithms.

The value of feedback for LTE resource allocation

The LTE cellular network is designed for meeting the requirements of a broad range of applications in very dynamic conditions. This explains its great flexibility in resource allocation. In order to provide the mobile stations with the exact required services, the base station relies on feedback information reported by each mobile station. In this paper, several feedback reduction schemes are analysed and compared, for a broad range of LTE resource allocation schemes and deployment scenarios, by means of simulation and a quantitative cost model. It is concluded that feedback reduction should be adapted to the scenario, as function of users, resource allocation strategy or channel properties, and up to 139% gain in overall throughput can be obtained by doing so.

Localization in long-range ultra narrow band IoT networks using RSSI

Internet of things wireless networking with long-range, low power and low throughput is raising as a new paradigm enabling to connect trillions of devices efficiently. In such networks with low power and bandwidth devices, localization becomes more challenging. In this work we take a closer look at the underlying aspects of received signal strength indicator (RSSI) based localization in UNB long-range IoT networks such as Sigfox. Firstly, the RSSI has been used for fingerprinting localization where RSSI measurements of GPS anchor nodes have been used as landmarks to classify other nodes into one of the GPS nodes classes. Through measurements we show that a location classification accuracy of 100% is achieved when the classes of nodes are isolated. When classes are approaching each other, our measurements show that we can still achieve an accuracy of 85%. Furthermore, when the density of the GPS nodes is increasing, we can rely on peer-to-peer triangulation and thus improve the possibility of localizing nodes with an error less than 20m from 20% to more than 60% of the nodes in our measurement scenario. 90% of the nodes is localized with an error of less than 50m in our experiment with non-optimized anchor node locations.

Exploration of User Separation Capabilities by Distributed Large Antenna Arrays

In this paper, we present a novel exploration of spatial separation of closely-located users by a massive MIMO system in line-of-sight (LoS) for both an anechoic chamber and an indoor corridor propagation environments. A distributed massive multiple-input multiple-output (DM-MIMO) system powered by software defined radios (SDRs) has been used for the measurement campaign. For the user separation study, we first conduct an analysis with a spherical wave channel model for physically-large rectangular arrays. Preliminary simulation results show that a single antenna array achieves better user separation for users distributed on a line parallel to the array plane rather than when users are distributed on a line normal to the array. An intuitive idea is that, by splitting a collocated antenna array into two subarrays, additional diversity is created if the second sub-array is on a plane orthogonal to the first sub-array. Figures of merit such as the correlation coefficients, condition numbers and sum-rates of both centralized and distributed antenna arrays have been chosen to determine the impact of array split and positioning on user separation. Extensive measurements, performed on two 32-element antenna arrays of a massive MIMO testbed at 2.6GHz, show that an improvement of around 140% can be achieved in a poor scattered environment if distributed arrays are used instead of centralized ones.

Scalable LTE interference mitigation solution for HetNet deployment

Interference management has become an important concern for the wireless community over the years. This is especially important in the context of LTE, which relies on OFDMA and dense frequency reuse. Different techniques for inter-cell interference coordination are available in literature but most of them make use of static methods, which cannot adapt to a load changing network or heavily complex centralized systems which present an obstacle for future scalability. Furthermore the addition of heterogeneous components, such as femtocells, has incremented the inter-cell interference problem even more. Given the unpredictable nature of femtocells and the fact that no communication mechanism is envisioned between macrocells and femtocells, the inter-cell interference problem needs to be addressed in two separate ways. In this paper we analyze a heterogeneous LTE OFDMA downlink network and we propose a low-complexity, distributed interference mitigation method which is aware of network load and propagation conditions. The method is fully scalable and addresses the macro-to-macro and the femto-to-macro interference separately. The proposed method makes use of the iterative Hungarian algorithm, which effectively reduces interference and enhances the quality of service of starved user when compared to other state of the art solutions.

Coverage and Power Gain of Aerial Versus Terrestrial Base Stations

Aerial stations have been recently recognized as an attractive alternative to provide wireless services to terrestrial users thanks to their superior coverage capability. In this paper, the coverage and power gain that can be achieved by a drone with respect to a terrestrial base station are studied. We address the problem by characterizing the coverage area based on the network outage probability, taking into account the height depending fading and path loss exponent that characterize air-to-ground wireless links. Results show that there exist a unique optimal altitude that provides the largest coverage and power gain, which strikes a fine balance between the path loss, due to the higher altitude, and a reduced influence of the multipath scattering. While numerical evaluations show that even at low altitudes the network gains up to 4x coverage or 20 dB power, the gain achieved at optimal altitude can be higher

Ultra-Reliable IEEE 802.11 for UAV Video Streaming: From Network to Application

Civilian application of Unmanned Aerial Vehicles (UAVs) are becoming more and more widespread. An important question is how ultra-reliable communication to and from the drone will be organised. At the moment complex and difficult to deploy point-to-point proprietary wireless links are often used. To enable ubiquitous usage of UAVs it is necessary to have a simple, reliable and widely available data link, such as IEEE 802.11. In this work we examine if infrastructure to control UAVs could be built from IEEE 802.11 access points already deployed for other applications. Our conclusions are based on a combination of measurements and simulations. The analysis presented assumes, but is not limited to, a representative UAV mission that involved streaming video to the ground. The proposed framework then significantly improves reliability by allowing the UAV to broadcast to multiple ground receivers and solves the limited acknowledgment available to the aerial node by applying FEC at the application layer.

Exploiting transport-block constraints in LTE improves downlink performance

Efficient resource allocation is necessary to provide the users with the quality of service promised in modern cellular networks, such as LTE. Traditional allocation methods make use of the smallest granularity available, the physical resource block (PRB), to assign resources to each user. The selected resources assigned to a user form a transport block (TB). However, the standard constrains the use of only one modulation and coding rate per TB. This forces the channel quality of the resources to be averaged across the TB, in order to determine the best modulation and coding scheme. In state-of-the-art systems, a non-linear heuristic is used in order to perform this averaging. Unfortunately, when bad PRBs are present next to good ones, this strategy is not optimal. We show that dropping the worst PRBs can improve the performance while remaining standard-compliant. We propose a simple algorithm that can be overlaid to any existing solution and we analyse its effect on multiple state-of-the-art schedulers. A gain is obtained both in throughput (up to 8% increase) and in power consumption (up to 23% reduction).

Tuning the Longley-Rice propagation model for improved TV white space detection

The secondary use of the frequency band below 1 GHz is gaining a lot of interest for wireless communications due to the attractive propagation characteristics in this band. Optimal reuse relies partially on the reliable detection of unused channels. We propose to detect unused channels based on prediction with the Longley-Rice channel model of which the parameters are tuned thanks to a limited amount of measurements with a low-cost, low-power sensing device.