Measurement reporting is essential in every cellular network to guarantee the best radio resource management and performance to its users. The information in reports is mainly used to perform handovers and interference management between cells. In the case of cellular-connected UAVs, where the UAV impacts a high number of cells due to its flight height, measurement reporting becomes essential. However, applying the same reporting schemes used for terrestrial users, the UAV appears to generate a large number of reports, creating a substantial signalling overhead. To overcome this problem, we introduce in this paper a new measurement reporting scheme adapted for UAVs, which reduces the number of reports compared to LTE-supported aerial vehicles. Our scheme shows a 30% reduction in number of reports compared to LTE, without having a major impact on the network’s knowledge about the most relevant cells.

We focus in this paper on Cellular-connected Uncrewed Aerial Vehicles (UAVs) in a scenario of a camera-equipped UAV, streaming a live event. The UAV coexists with a large number of ground User Equipment (gUEs) belonging to people attending the same event, and using the network to transmit their data. Hence the cellular network must satisfy the high data rate demand of both the UAV and gUEs. For that, we explore interference mitigation solutions, and propose a novel algorithm for UAV cell-selection which minimizes the impact of the UAV to the concerned serving cell. The results demonstrate an uplink data-rate gain of 32% for gUEs in the crowded cell, compared to the standard algorithm, while achieving a target UAV throughput of 20 Mbps. This comes at a cost of increased UAV transmission power of 50% and a slight data rate degradation for gUEs in neighboring cells, up to 13%.

Uplink power control plays a significant role in maintaining a good signal quality at the serving cell while minimizing interference to neighboring cells, thus maximizing the system performance. Traditionally, a single value open-loop power control (OLPC) parameter, P0, is configured for all the user equipments (UEs) in a cell, and often same setting is used for similar cells. Recent studies have demonstrated that optimal P0depends on many factors, which yields a complex multidimensional optimization problem and there are no efficient approaches known to solve it under practical system-level settings. In this paper, we propose a solution based on reinforcement learning (RL) where each BS autonomously adjusts its P0setting to maximize its throughput performance. As compared to conventional sub-optimal approach, our solution encompasses a smart clustering of UEs, where each cluster specifies its own P0. The proposed solution is evaluated by extensive system level simulations, where our results demonstrate a potential performance enhancement as compared to the baseline proposals.

One of the key enablers for the use of cellular networks to provide connectivity to Unmanned Aerial Vehicles (UAVs) is reliability assurance. Estimating accurately the expected service availability and reliability that a UAV will experience along a planned route, helps to avoid critical situations. In this paper, we evaluate the use of a data-driven approach to estimate the expected serving signal level of a UAV planning to fly along a specific path. The estimation approach, presented in a previous study for the ground-level case, is based on the aggregation of measurements of UAVs that have previously been flying along the same route. Using this approach we achieve an estimation error as low as 2.7 dB. Based on the estimations we calculate the expected outage probability in terms of service availability and reliability and provide estimations of the expected critical areas along the route. Results show that 90% of the availability and 65% of the reliability critical areas in the route can be accurately estimated.

Estimating accurately the signal levels that a user equipment experiences along a movement route is a key step in the process of providing and guaranteeing the required service quality. Obtaining accurate location-specific estimations of the signal level is challenging due to its random variations. In this paper we investigate the use of aggregated measurements from multiple User Equipments (UE) to estimate the serving Reference Signal Received Power (RSRP) that the user will experience along a route. We use LTE measurements obtained in rural and urban areas from drive tests and analyze the dependence of data variability. Results show that the accuracy of data-driven estimation is impacted significantly by the variability in the underlying data due to UE orientation, UE characteristics and their immediate environment. With compensation for a subset of these effects the standard deviation of the estimation error can be lowered from an overall approximately 8 dB down to 4dB.

Cellular-connected unmanned aerial vehicles (UAVs) have recently attracted a surge of interest in both academia and industry. Understanding the air-to-ground (A2G) propagation channels is essential to enable reliable and/or high-throughput communications for UAVs and protect the ground user equipments (UEs). In this contribution, a recently conducted measurement campaign for the A2G channels is introduced. A uniform circular array (UCA) with 16 antenna elements was employed to collect the downlink signals of two different Long Term Evolution (LTE) networks, at the heights of 0-40m in three different, namely rural, urban and industrial scenarios. The channel impulse responses (CIRs) have been extracted from the received data, and the spatial, including angular, parameters of the multipath components in individual channels were estimated according to a high-resolution-parameter-estimation (HRPE) principle. Based on the HRPE results, clusters of multipath components were further identified. Finally, comprehensive spatial channel characteristics were investigated in the composite and cluster levels at different heights in the three scenarios.

5G networks should support heterogeneous services with an efficient usage of the radio resources, while meeting the distinct requirements of each service class. We consider the problem of multiplexing enhanced mobile broadband (eMBB) traffic, and grant-free ultra-reliable low-latency communications (URLLC) in uplink. Two multiplexing options are considered; either eMBB and grant-free URLLC are transmitted in separate frequency bands to avoid their mutual interference, or both traffic share the available bandwidth leading to overlaying transmissions. This work presents an approach to evaluate the supported loads for URLLC and eMBB in different operation regimes. Minimum mean square error receivers with and without successive interference cancellation (SIC) are considered in Rayleigh fading channels. The outage probability is derived and the achievable transmission rates are obtained based on that. The analysis with 5G new radio assumptions shows that overlaying is mostly beneficial when SIC is employed in medium to high SNR scenarios or, in some cases, with low URLLC load. Otherwise, the use of separate bands supports higher loads for both services simultaneously. Practical insights based on the approach are discussed.

In this work, we analyze the end-to-end latency measured in a client-server application that emulates the traffic requirements for the Unmanned Aerial Vehicle (UAV)'s Command and Control (C2) link. The connectivity is provided by two real LTE-A networks to a client attached to a flying UAV. Measurements are performed at 4 different heights: ground level, 15 m, 40 m and 100 m. In single operator scenarios, the reliability measured at the target latency, 50 ms, was between 99.6 % and 97.6 % in downlink, and 91.3% and 99.4% in uplink. These results are below the 99.9 % target reliability defined for UAVs and they show that several consecutive packets can be missed when the radio link connectivity degrades, leading to high (> 1 s) values for the 99.9%-ile of latency. To circumvent this, a dualoperator hybrid access scheme is proposed in this paper. The results show that the hybrid access strategy managed to reach the performance requirements in most cases. The solution shows potential to enable C2 over cellular networks, without requiring optimization or modifications in the network.

Cellular networks based on current LTE Advanced or coming 5G technology, constitute an attractive candidate to provide communication links for drones in low level airspace. This paper extends previous findings on path loss exponent and shadow fading variation for an urban environment, by adding new and more extensive empirical evidence. Specifically, by way of the measurements methodology we study also the spatial correlation of the shadow fading, including the lateral spatial autocorrelation (decorrelation distance) and the cross-correlation in shadowing variability between different heights. Data was obtained with the use of a drone flying at heights up to and above rooftop, using a radio network scanner measuring live LTE signals at 1800 MHz. The path loss analysis confirmed the validity of previously presented modelling frameworks for the behaviour versus height, as well as the characteristics of the increased interference observed when the drone if above rooftop level. As for the spatial correlation of the shadow fading, the results indicate that decorrelation distance does not change appreciably from ground level up to and above rooftop level, and remains in the order of 10 m. The shadow fading variability is generally uncorrelated versus height, although with a trend to be correlated below rooftop level, but not above.

Although the use of cellular networks to serve drones has been investigated in several recent works, the path loss or shadowing variation is still relatively unexplored. The variation and its dynamic behaviour is of importance in characterizing the reliability of the drone communication link, but difficult to assess by experimental means on a large scale. The main goal of this paper is to study the feasibility of ray tracing models to accurately predict shadow fading variations at different heights, so that the shadow fading correlation distances for the UAV channel can be found in both vertical and horizontal directions, without the need of performing extensive field measurement campaigns. For that, predictions obtained through a ray tracing tool are compared to field measurements in an urban scenario. Our results show that with accurate 3D maps, the tool is useful for predicting the dynamics of the UAV propagation channel, and therefore can be used partly as a substitute for field measurements.

In this paper, we discuss the achievable transmission rates over collision-prone radio resources shared by a number of devices, representative of novel Internet-of-Things (IoT) scenarios. We consider Maximum Ratio Combining (MRC) and Minimum Mean Square Error (MMSE) receivers at the base station, and derive the relationship between target failure probability and saturation rate, which represents the maximum achievable rate over shared resources in the interference limited regime. MRC receiver is shown to be sensitive to the presence of statistically relevant interferers operating over the same resources, rapidly leading to rate saturation. The MMSE receiver adds a tier of protection to collisions thanks to its interference suppression capabilities, suffering for a rate penalty only in case of a high number of users. A realistic system analysis in an indoor hotspot scenario validates the analytical trends and suggests insights on practical link adaptation strategies.

Mobility performance is at the heart of each cellular technology, including omni-present LTE networks. It becomes even more significant when such system is supposed to reliably support state-of-the-art devices, such as Unmanned Aerial Vehicles (UAVs), emerging at rapid pace in our surroundings. Contemporary network deployments, addressing mainly the needs of terrestrial users, were not optimized to serve UAVs moving below and above the typical cellular antenna heights. Thus, it is worth checking how they can handle these novel and distinctive services, also with respect to mobility robustness. This paper elaborates on the challenges ahead which must be tackled to make existing LTE networks sufficiently capable of accommodating Aerial Vehicles. We present simulation results in various environments, obtained for different user equipment's (UE's) heights and velocities. Furthermore, we describe and analyze the identified issues. Finally, we also suggest potential optimizations and future research goals.

Ultra-reliable and low latency communication (URLLC) presents the most challenging use cases for fifth generation (5G) mobile networks. Traditionally the focus for mobile broadband has been to optimize the system throughput for high speed data traffic. However the optimization criteria for URLLC should focus on achieving small packets transmissions under strict targets such as 99.999% reliability within 1 ms. Power control is one candidate technology component for improving reliability and latency. In this work we investigate the power control for grant-free URLLC transmissions through extensive system level simulations in a urban outdoor scenario. We initially compare different settings for open loop power control (OLPC) with full and with fractional path loss compensation. Then we evaluate whether power boosting the retransmission can reduce the probability of packets delays under the 1 ms constraint. We also discuss the practical implication of applying power boosting. With full path loss compensation and boosting retransmissions, we show that a URLLC load such as 1200 small packets per second per cell can be achieved in the considered scenario.

This paper focus on the investigation of aerial communications for drones connected to cellular networks in urban areas. Most of the previous measurement based channel models for urban environments do not extend to users located at heights above rooftops. On the other hand, UAVs are expected to fly at the very low level (VLL) airspace, in heights much lower than those covered by previous air-to-ground models. By means of field measurements, this paper presents height-dependent closed form expressions for the urban channel model (path loss slope and shadowing) extending to heights up to 40 m and compares the observed results with 3GPP reference models and previous studies. Measurements were conducted by a radio scanner attached to a construction-lift to measure the radio signal from three different live LTE networks (800, 1800, and 2600 MHz). Results suggest radio path clearance increases with height. As a consequence, it leads to an increase in number of cells in the detectable range and in the set of neighbors within 3 dB of the serving cell in the receiver, indicating neighbor cells are closer to each other in the power domain.

This paper provides an updated analysis of link-budget and coverage performance for LTE IoT technologies: enhancements for machine type communications (eMTC) and narrowband Internet of Things (NB-IoT). Previous studies have used the 3GPP evaluations assumptions and have demonstrated the coverage capabilities of these technologies when they are independently deployed. Some operators are, however, likely to deploy dual-mode networks - eMTC and NB-IoT - with the intent of supporting different applications in the two systems. With all conditions being equal for the two systems in such a scenario, comparison of the eMTC and NB-IoT technologies then requires that all assumptions are aligned. This paper extends the previous studies with the assumptions aligned for eMTC and NB-IoT systems to provide a fair coverage performance comparison. The study shows that compared to the 3GPP assumption, under the aligned assumptions, both eMTC and NB-IoT can support up to 5dB and 3dB higher uplink coverage, respectively. We further show these link budget improvements yield significantly reduced LTE IoT coverage outage in two simulated scenarios based on real network deployments: a wide area rural case and an urban deep indoor case. The results further demonstrate the potential of these LTE IoT technologies in realistic network deployment conditions.

Unmanned Aerial Vehicles (UAVs) are expected to be connected through cellular networks. As the radio characteristics are different for airborne UEs compared to terrestrial UEs, it is beneficial to identify whether a UE is airborne (on a UAV) or on the ground, such that interference and mobility management can be optimized for UAVs separately from terrestrial UEs. In this paper, we present a classification algorithm using existing LTE UE radio measurements to identify whether a UE is airborne or terrestrial. The method is verified with LTE measurements made in a rural area at different heights, including terrestrial measurements and it is shown that the method in 3 out of the 4 different measurement cases can detect a UE to be airborne with 99% likelihood, while the fourth case still can classify a UE correctly in 95% of the cases. The right classification can further be improved by taking multiple consecutive samples into account before making a classification decision.

This paper analyzes the radio channel between cellular network and Unmanned Aerial Vehichles (UAVs). The assessment is done by means of field measurements performed in a rural environment in Denmark. The tests were conducted in an operating LTE network (800 MHz), using a commercial cell phone placed inside the frame of a winged UAV. Trials were conducted with UAV flying at 5 different heights measured above ground level (20, 40, 60, 80 and 100m) and a pathloss regression line was obtained from the results. Thereafter, an analysis of downlink (DL) interference is performed for the reported measurements, which suggests that there is a height-related degradation on signal-to-interference levels. Three possible sources for this effect are also presented and discussed in this paper: expanded radio horizon at higher levels, line-of-sight (LOS) clearing and decreased obstruction of the first Fresnel zone. The importance of a better quantification of these factors are stressed as future work plans are described.

The use of Unmanned Aerial Vehicles (UAV) for civilian and commercial services has experienced a significant increase in the past couple of years. Emerging UAV enabled services, however, require extended beyond-visual-line-of-sight geographical range. One key regulatory requirement for these services is that the radio communication link must reliably cover a wide(er) area, when compared to the visual-line-of-sight range radio links currently used. Standardized cellular systems such as Long Term Evolution UMTS (LTE), are an obvious candidate to provide the radio communication link to UAVs. In this paper, we use empirical measurements in live rural LTE networks to assess the impact of uplink and downlink radio interference on the UAV radio connectivity performance. Further, we provide a baseline analysis on the potential of interference mitigation schemes, needed to provide a reliable radio connectivity to the UAVs.

In this simulation work the coverage of GPRS, Narrowband-IoT, LoRa, and SigFox is compared in a realistic scenario, covering 7800 km2 and using Telenor's commercial 2G, 3G, and 4G deployment. The target is to evaluate which of the four technologies provides the best coverage for Internet of Things devices, which may be located deep indoor. The results show that Narrowband-IoT, having the best Maximum Coupling Loss performance of 164 dB, also provides the best coverage. This is despite the fact that LoRa and SigFox deployments with omnidirectional antennas are found to provide 3 dB lower link loss on average. In the deployment 11 % of the geographical area contains devices, located both in rural and urban areas. The NB-IoT has an outage below 1 % for locations experiencing 20 dB indoor penetration loss in addition to the outdoor path loss. SigFox performs similarly, while LoRa cannot provide coverage for 2 % of those locations. For the challenging deep indoor case, where 30 dB additional penetration loss is expected, NB-IoT has 8 % outage while SigFox and LoRa is unable to cover 13 % and 20 % of the locations. The four technologies may not be deployed at all existing site locations and therefore the work also includes a study of the coverage as a function of the minimum Inter-Site Distance, where sites closer than 2, 4, and 6 km are filtered out. The results show that SigFox and NB-IoT have outage probabilities below 5 % even though sites closer than 4 km are removed from the simulations.

One of the key ingredients of Intelligent Transportation Systems (ITS) is delivery of broadcast status messages among vehicles for safety purposes. This requires an efficient Medium Access Control (MAC) that provides low average delay and high reliability. To this end, Carrier Sense Multiple Access (CSMA) has been commonly proposed for Vehicle Ad Hoc Networks (VANETs). Nevertheless, the hidden- node problem can jeopardize the reliability of CSMA, whereas the latency when accessing the channel can be unbounded. To overcome these limitations, resource allocation based on the geo-location of the vehicles can be applied in VANETs. For example, a distributed location based access (DLOC) algorithm has been proposed such that vehicles access orthogonal resource blocks based on their position, aiming at maximizing the distance of co-channel transmitters. In this paper we propose a stochastic geometry approach to analyze DLOC taking into account path loss and fading as well as the random location of transmitting vehicles. Analytical results include the average interference, average binary rate and capture probability, i.e. probability of successful message transmission. It is shown that increasing the number of RBs increases reliability but there is a trade off between reliability and average BR.

In this paper we investigate the ability of Long- Term Evolution (LTE) network to provide coverage for Unmanned Aerial Vehicles (UAVs) in a rural area, in particular for the Command and Control (C2) downlink. The study takes into consideration the dependency of the large-scale path loss on the height of the UAV, which is derived from actual measurements, and a real-world cellular network layout and configuration. The results indicate that interference is the dominant factor limiting the cellular coverage for UAVs in the downlink: outage level increases from 4.2% at 1.5m height to 51.7% at 120m under full load condition. Lower network loads or larger inter-site distances reduces the interference and thus improves the coverage significantly: outage at 120m is reduced to only 1.9% under network load of 25% for example. Similar effects are expected to be achievable by static or dynamic interference coordination schemes. In addition, ideal Interference Cancellation (IC) scheme with ability to remove completely the dominant interferer shows less effective for UAVs than for users on the ground. On the other hand, macro network diversity has very good potential for drones, as not only it improves the coverage, but also the reliability of the C2 link.

In this paper we set out to analyze the indoor capacity under a realistic high-rise building scenario. The study takes into consideration the number of indoor cells deployed per floor, different inter-site distances (ISDs), transmit power settings and outdoor macro interference levels. The outcome shows large variation in performance gain just by optimizing indoor cell locations, highlighting the need for thorough indoor radio planning. Investing into more indoor cells helps to increase capacity, and also to cope better with outdoor interference, but the gain tends to be diminishing due to the increase of inter-cell interference (ICI). Increasing transmit power brings largest gain when the density of indoor cell is low, and the noise and/or outdoor interference is the dominant source of performance degradation. When analyzing performance gain of an ideal receiver-side Interference Cancellation (IC) algorithm, the study also shows that, if the Dominant Interferer Removal (DIR) rate is below 50%, doubling the number of indoor cells would bring better capacity gain than investing into such an IC receiver.

Big expectations are put into vehicular communications (V2X) for a safer and more intelligent driving. With human lives at risk, the system cannot afford to fail, which translates into very stringent reliability and latency requirements to the radio network. One of the challenges is to find efficient radio resource management (RRM) strategies for direct vehicle-to-vehicle (V2V) communication that can fulfil the requirements even with high traffic density. In cellular networks, a device-to-device (D2D) communication is usually split into two phases: the discovery process, for node awareness of each other; and the communication phase itself, where data exchange takes place. In the case of V2V, the discovery phase can utilize the status information that cars broadcast periodically as the beacons to detect the presence of neighbouring cars. For the delivery of specific messages (e.g., a hazardous event), direct communications can then be set up in a very fast way, based on the previously collected information. Several aspects have been revealed as essential to ensure the reliability and latency requirements of the discovery, such as the autonomous selection of the resources, the duplexing mode and the interference cancellation receivers

Indoor deployments for providing coverage and capacity inside buildings is an attractive option for cellular network operators as most of the traffic in today's cellular networks is generated indoors. This paper studies the benefit of indoor traffic offloading on the overall network capacity using a new method that allows assessing the network performance gains considering different levels of traffic offloading without the need to decide beforehand which buildings to deploy the indoor solutions in or the exact type of indoor solution used in each building. Using this method, we evaluate the impact of different amounts of indoor traffic offload and the performance of three different indoor deployment strategies on a study case network selected as a typical real world ultra dense urban area. The results show that choosing the most cost-effective buildings (lowest cost per traffic offload) first in the indoor deployment plan leads to highest network capacity gains for the same level of investment.

In this paper the coverage and capacity of SigFox, LoRa, GPRS, and NB-IoT is compared using a real site deployment covering 8000 km2 in Northern Denmark. Using the existing Telenor cellular site grid it is shown that the four technologies have more than 99 % outdoor coverage, while GPRS is challenged for indoor coverage. Furthermore, the study analyzes the capacity of the four technologies assuming a traffic growth from 1 to 10 IoT device per user. The conclusion is that the 95 %-tile uplink failure rate for outdoor users is below 5 % for all technologies. For indoor users only NB-IoT provides uplink and downlink connectivity with less than 5 % failure rate, while SigFox is able to provide an unacknowledged uplink data service with about 12 % failure rate. Both GPRS and LoRa struggle to provide sufficient indoor coverage and capacity.

In this measurement study the signal activity and power levels are measured in the European Industrial, Scientific, and Medical band 863-870 MHz in the city of Aalborg, Denmark. The target is to determine if there is any interference, which may impact deployment of Internet of Things devices. The focus is on the Low Power Wide Area technologies LoRa and SigFox. The measurements show that there is a 22-33 % probability of interfering signals above -105 dBm within the mandatory LoRa and SigFox 868.0-868.6 MHz band in a shopping area and a business park in downtown Aalborg, which thus limits the potential coverage and capacity of LoRa and SigFox. However, the probability of interference is less than 3 % in the three other measurement locations in Aalborg. Finally, a hospital and an industrial area are shown to experience high activity in the RFID subband 865-868 MHz, while the wireless audio band 863-865 MHz has less activity.

In this paper we analyze and discuss the coverage and capacity of Sigfox and LoRaWAN in a large scale urban environments covering 150 km$^2$ in Northern Denmark. First, the study measures and analyzes interference in the European 868 MHz license free industrial, scientific, and medical band, creating a model for the interference. The measured interference in downtown Aalborg has an occurrence rate of 22 % and a generalized extreme value distributed power level. Next, the study compares the coverage of the two Internet of Things network solutions using the existing Telenor cellular site grid both with and without interference from the measured external sources. The study concludes that without interference, both LoRaWAN and Sigfox provides very good indoor coverage of more than 99 %. Furthermore, Sigfox and LoRaWAN can provide uplink and downlink failure rates of less than 1 % for the 95 percentile of the devices for all cells without external interference. Adding the external interference results in an outdoor coverage of 90- 95 % and indoor coverage of 50-80 %. Finally, the uplink and downlink 95 percentile failure rate increases significantly to 50 % for LoRaWAN and exceeds 60 % for Sigfox.

The 3GPP has introduced the LTE-M and NB-IoT User Equipment categories and made amendments to LTE release 13 to support the cellular Internet of Things. The contribution of this paper is to analyze the coverage probability, the number of supported devices, and the device battery life in networks equipped with either of the newly standardized technologies. The study is made for a site specific network deployment of a Danish operator, and the simulation is calibrated using drive test measurements. The results show that LTE-M can provide coverage for 99.9 % of outdoor and indoor devices, if the latter is experiencing 10 dB additional loss. However, for deep indoor users NB-IoT is required and provides coverage for about 95 % of the users. The cost is support for more than 10 times fewer devices and a 2-6 times higher device power consumption. Thus both LTE-M and NB- IoT provide extended support for the cellular Internet of Things, but with different trade- offs.

In this paper we address the channel modeling aspects for a deep-indoor scenario with extreme coverage conditions in terms of signal losses, namely underground garage areas. We provide an in- depth analysis with regard to the path loss (gain) and large-scale signal shadow fading, and propose a simple propagation model which can be used to predict cellular signal levels in similar deep- indoor scenarios. The measurement results indicate that the signal at 800 MHz band penetrates external concrete walls to reach the lower levels, while for 2000 MHz wall openings are required for the signal to propagate. It is also evident from the study that the shadow fading at different levels of an underground garage are highly correlated. The proposed frequency-independent floor attenuation factor (FAF) is shown to be in range of 5.2 dB per meter deep.

This paper investigates the propagation characteristics of the urban macro cells at centimeter-wave (cmWave) frequencies, in particular at 10, 18 and 28 GHz. The measurements are performed at several transmitter (Tx) locations and heights, in both line-of-sight (LOS) and non line-of-sight (NLOS) conditions, and with distances up to 1,400 m. The distancedependent mean path loss and shadow fading standard deviation (std) are extracted for all cases based on a single-slope path loss model, and offered here for quick determination of link budget and system capacity. The results show the potential usage of the cmWave band for mobile cellular services in the years to come: the NLOS path loss slopes at 10 and 18 GHz are not much different from the 2 GHz reference, and the corresponding offsets are in the order of 20-23 dB for 25 m Tx height. This gap is expected to be overcome by the usage of high-gain miniaturized steerable antennas, which is feasible due to the reduced antenna aperture size at the cmWave band. Similar to the 2 GHz band, the NLOS shadow fading std for cmWave is within 6 dB. The effect of Tx height is clearly shown in the NLOS scenario: at 10 GHz, for example, 7.5 dB reduction in attenuation could be achieved by raising the Tx antenna from 15 m (below average roof-top) to 25 m (above roof-top), or 23.4 dB if the Tx height is elevated to 54 m.

This paper presents and compares two candidate large-scale propagation path loss models, the alpha-beta-gamma (ABG) model and the close-in (CI) free space reference distance model, for the design of fifth generation (5G) wireless communication systems in urban micro- and macro-cellular scenarios. Comparisons are made using the data obtained from 20 propagation measurement campaigns or ray- tracing studies from 2 GHz to 73.5 GHz over distances ranging from 5 m to 1429 m. The results show that the one-parameter CI model has a very similar goodness of fit (i.e., the shadow fading standard deviation) in both line-of-sight and non-line-of-sight environments, while offering substantial simplicity and more stable behavior across frequencies and distances, as compared to the three-parameter ABG model. Additionally, the CI model needs only one very subtle and simple modification to the existing 3GPP floating-intercept path loss model (replacing a constant with a close-in free space reference value) in order to provide greater simulation accuracy, more simplicity, better repeatability across experiments, and higher stability across a vast range of frequencies.

It is becoming clear that 5G wireless systems will encompass frequencies from around 500 MHz all the way to around 100 GHz. To adequately assess the performance of 5G systems in these different bands, path loss (PL) models will need to be developed across this wide frequency range. The PL models can roughly be broken into two categories, ones that have some anchor in physics, and ones that curve- match only over the data set without any physical anchor. In this paper we use both real-world measurements from 2 to 28 GHz and ray-tracing studies from 2 to 73.5 GHz, both in an urban-macro environment, to assess the prediction performance of the two PL modeling techniques. In other words, we look at how the two different PL modeling techniques perform when the PL model is applied to a prediction set which is different in distance, frequency, or environment from a measurement set where the parameters of the respective models are determined. We show that a PL model with a physical anchor point can be a better predictor of PL performance in the prediction sets while also providing a parameterization which is more stable over a substantial number of different measurement sets.

The objective of this paper is to propose traffic steering solutions that aim at optimizing the end- user throughput. Two different implementations of an active mode throughput-based traffic steering algorithm for Heterogeneous Networks (HetNet) are introduced. One that always forces handover of the active users towards the cell offering the highest throughput, and a second scheme that aims at maximizing the systems sum throughput. Results show that the first option brings the best performance at the cost of more than three handovers per user per second for high-load cases. The second option offers slightly lower traffic steering gains at a considerably lower cost in terms of number of handovers. The gain in terms of increased average session throughput for the second option equals 32% at low-load, 18% at medium-load, and 7% at high-load conditions. The gain in the fifth percentile user session throughput is generally higher, reaching values of 36% and 18% for the medium- and high-load conditions.

This paper studies LTE (Long-Term Evolution)-Advanced heterogeneous network expansion in a dense urban environment for a 1000 times capacity increase and a 10 times increase of the minimum user data rate requirements. The radio network capacity enhancement via outdoor and indoor small cell densification and utilization of the higher frequency bands has been investigated. As the baseline, we assume a full LTE-Advanced network deployment. Rather than looking at peak data rate, we focus on the end-user experience defined as 90% coverage at a minimum user data rate. We conclude that the 1000 times network capacity increase together with the 10 times increase of minimum user data rate can be reached by LTE-Advanced deployment with approximately 10 times more outdoor micro sites and 100 times more indoor femto cells with respect to the number of macro sites. In terms of spectrum requirements, we have increased the total amount of downlink spectrum to a total of 300 MHz by re-farming spectrum and adding new spectrum in 3.5 GHz band. We conclude that new spectrum at 3.5 GHz is essential to reach the set target network capacity.

This paper studies indoor Wi-Fi IEEE 802.11ac deployment as a capacity expansion solution of LTE-A (Long Term Evolution-Advanced) network to achieve 1000 times higher capacity. Besides increasing the traffic volume by a factor of x1000, we also increase the minimum target user data rate to 10Mbit/s. The objective is to understand the performance and offloading capability of Wi-Fi 802.11ac at 5GHz. For the performance evaluation of Wi-Fi, we propose a novel analytical throughput model that captures both key 802.11ac enhancements and multi-cell interference. We provide a quantitative evaluation of large-scale indoor Wi-Fi 802.11ac deployment in a real urban scenario by extensive simulations. We conclude that deploying indoor Wi-Fi access points in almost every building is essential to carry the x1000 traffic volume and ensure a minimum user data rate of 10Mbit/s.

Next generation wireless networks aim at a significant improvement of the spectral efficiency in order to meet the dramatic increase in data service demand. In local area scenarios user- deployed base stations are expected to take place, thus making the centralized planning of frequency resources among the cells, a non-viable solution. Cognitive Radio (CR) and Dynamic Spectrum Access (DSA) are the research paradigms which are expected to provide the network nodes the capabilities for an autonomous and efficient selection of the spectrum resources. In this paper we present the first experimental activities with the Autonomous Component Carrier Selection (ACCS) algorithm, a distributed solution for interference management among small neighboring cells. A preliminary evaluation of the algorithm performance is provided considering its live execution on a software defined radio network testbed. The obtained experimental results confirm the performance trends obtained from prior simulation studies. The analysis in dynamic environment conditions also allowed identifying the utilization of static thresholds in the decision making process, as a critical aspect for the optimization of network capacity.

The main objective of the paper is to investigate and compare the downlink performance of different LTE heterogeneous network (HetNet) deployment solutions. By adding small cells to the existing macro overlay, network coverage and capacity can be significantly enhanced to accommodate the fast growth of mobile broadband traffic. Emphasis is put on how to optimally assign the spectrum for the different networks layers in an evolved HetNet including outdoor and indoor small cells. The study is conducted for a "Hot-Zone" scenario, i.e. a high-traffic area within a realistic dense urban deployment. A broadband traffic volume growth by a factor of 50 compared to today's levels is assumed. The investigated deployment schemes are outdoor pico-only, indoor femto-only and joint pico-femto deployments, all combined with an overlay macro layer. The results indicate that the best network coverage performance with a minimum user data rate of 1 Mbps is achieved when deploying small cells on dedicated channels rather than co-channel deployment. Furthermore, the joint pico and femto deployment turns out to be the right trade-off between increased base station density and enhanced network capacity.

This paper investigates the downlink performance of indoor deployed Wi-Fi and Femto as the offloading solution to the LTE macro cellular networks in a realistic large-scale dense-urban scenario. With an assumed broadband traffic volume growth of 50x compared to today's levels, it is evaluated that a dual-carrier LTE macro network will not be able to provide sufficient service coverage with a 1 Mbps minimum data rate and, indoor coverage is identified as the major bottleneck.. We evaluate the performance of indoor Wi-Fi and Femto cell deployment to offload the congested LTE macro network. We show that, in a dual-carrier LTE macro case with a total of 30 MHz spectrum, Wi-Fi access point density of 230/km2 is required to meet the set target of 90% coverage with a minimum user data rate of 1 Mbps. For the same scenario it was found that an out-band Femto access point density of 1200/km2 is required. Furthermore, we show that in-band Femto cell cannot meet the set network requirement even at a very high access point density. We also show that Wi-Fi and Femto cell can offload the same amount of traffic when they are deployed at the same access point density.

In this paper we study the performance enhancement of a downlink LTE-Advanced system with a combination of the multi-user MIMO and carrier aggregation transmission techniques. Radio resource management for the systems with the combined features are proposed, and the system performance is evaluated. Extensive simulations with various traffic load condition from full buffer with fixed number of UEs to finite buffer with bursty traffic were considered in order to find out when and how these two features can support each other to improve the overall performance gain of the LTE-Advanced system. It is shown that MU-MIMO transmission technique can help to enhance the cell-edge performance of the CA system by 10%-40% depending on traffic load.

This paper addresses a method to estimate the multi user channel quality indicator (CQI) from the reported rank 1 single user CQI in LTE systems. We investigate the relationship between the multi user CQI and the channel condition. Based on that, we propose an updating mechanism where the estimated multi user CQI is varied according to the reported channel condition i.e. the rank 1 single user CQI. System performance of the proposed scheme is compared with the conventional fixed offset single user CQI estimation. System level simulation results show the efficiency of our proposed scheme with respect to both the enhancement in the system level performance and uplink overhead reduction. Using the statistic metrics derived from the system level simulation, we highlight the importance of having an accurate multi-user CQI estimation. The results illustrate how the multi user CQI information influence the packet scheduling and link adaptation decisions and ultimately the overall system performance.

This paper addresses the interference management problem in the context of LTE-Advanced femtocells. Due to the expected large number of user-deployed cells, centralized network planning becomes increasingly less viable. Consequently, we consider an architecture of autonomous decision makers. Our main contribution in this paper, denominated Generalized Autonomous Component Carrier Selection (G-ACCS), is a distributed carrier-based inter-cell interference coordination scheme that represents one step towards cognitive radio networks. The algorithm relies on expected rather than sensed interference levels. This approach facilitates scheduler-independent decisions, however, it can lead to overestimation of the interference coupling among cells when the resources are not fully utilized. Acknowledging this fact, G-ACCS leverages the power domain to circumvent the restrictive nature of expected interference coupling. This work focuses on the downlink and also provides an extensive characterization of the network performance as a function of the topology as well as the often overlooked temporal traits of traffic. We compare G-ACCS with other carrier-based solutions, including the simplest universal reuse strategy. The encouraging simulation results demonstrate that G-ACCS achieves an efficient and fair distribution of resources in all considered traffic and deployment conditions. More importantly, this is attained in a truly autonomous fashion, without any explicit parametrization.

In this paper we analyse the downlink performance of a rank adaptive multiple input multiple output (MIMO) system in a busty traffic cellular network. A LTE-Advanced system with multiple component carriers was selected as a study case. To highlight the advantage of using MIMO techniques, we used a single input multiple output (SIMO) system as a baseline for performance comparison. The gain mechanisms of the MIMO system over the SIMO system are investigated and their characteristic at different traffic load conditions are highlighted. The simulation results are used to verified our proposed model to predict the performance of the SIMO and MIMO systems in a bursty traffic network.

With exponential growth of mobile broadband traffic, mobile operators are facing the challenge of cost-efficiently evolving 3G/4G network to meet future network capacity demand. Heterogeneous multilayer network deployment is one essential performance-effective and potentially cost-effective candidate solution. We study optimal new site deployment algorithms in heterogeneous wireless cellular networks. We focus on a joint Macro and Micro layer new site deployment. We propose and evaluate a class of fast-convergent meta-heuristic algorithms: Scalable Multi-radio deployment AlgoRiThm (SMART). Their performances and convergence speeds are evaluated using a large-scale real dense-urban HSPA network deployment. We compare the performance on four variants of SMART: Greedy, Simulated Annealing, Greedy with memory and Simulated Annealing with memory. We show that the Simulated Annealing and Greedy algorithms achieve almost the same optimal deployment when the number of optimization iterations is large and, the Greedy algorithm converges much faster than Simulated Annealing algorithm when the number of optimization iterations is small. We also show that in a practical network deployment scenario SMART outperforms previous heuristic deployment algorithms proposed in the literature.

Market analyst research studies predict significant mobile data traffic increase over the next 5 to 10 years. The mobile network operators have to be able to meet these capacity demands by upgrading and optimizing their existing networks in parallel with the deployment of new radio access technologies. This paper proposes a mathematical modeling framework for the mobile broadband traffic growth to be employed in mobile network evolution studies. We show that an "S-curve" model based on the Gompertz function can be appropriately parameterized and provides sufficient flexibility for predicting various traffic growth scenarios. We exemplify the use of the proposed traffic modeling approach with a network evolution case study in the generic setting of a dense urban European network deployment scenario in combination with assumptions on the target network key performance indicator and user equipment receiver capabilities.

With full channel state information (CSI) available, it has been shown that carrier aggregation (CA) in the downlink can significantly improve the data rate experienced at the user equipments (UE) [1], [2], [3], [4]. However, full CSI feedback in all component carriers (CCs) requires a large portion of the uplink bandwidth and the feedback information increases linearly with the number of CCs. Therefore, the performance gain brought by deploying CA could be easily hindered if the amount of CSI feedback is not thoroughly controlled. In this paper we analyze several feedback overhead compression schemes in CA systems. To avoid a major re-design of the feedback schemes, only CSI compression schemes closely elated to the ones specified in LTE-Release 8 and LTE-Release 9 are considered. Extensive simulations at system level were carried out to evaluate the performance of these feedback schemes in various traffic load conditions. Different scenarios were considered to answer the questions of when and why these CSI feedback compression schemes can be applied in CA.

For the future LTE-Advanced network, one of the requirements in the uplink (UL) direction is to enhance the celledge user performances. Coordinated multi-point reception in the UL is one of the techniques being investigated to further improve the performance of LTE networks. With the help of the information coordination through the links between the sites and advanced receivers the UL performance can be improved. The simulation results show that, with the ideal interference cancellation, inter-Site maximum ratio combining, and optimized closed-loop and open-loop fractional power control, there are about 27% gains for the 5% outage user throughput and 12% gains for the average user throughput. As shown in this paper, these gains from UL macro-scopic multi-cell combining between sites are achieved for optimized power control, ideal interference cancellation receivers, and X2 with no delay and high bandwidth.

In the UTRAN long term evolution (LTE), the downlink data channel is shared among the active users through the orthogonal frequency division multiple access (OFDMA) technique, and high gains can be achieved by using dynamic packet scheduling. Control channels introduce an additional overhead, but also play a key role in exploiting such gains. This paper focuses on the physical downlink control channel (PDCCH) and introduces the main PDCCH related features which need to be analyzed in order to minimize its impact on the system performance.

This paper focuses on the Physical Downlink Control Channel (PDCCH) and describes the impact of its realistic constraints. Specifically, the impact on the performance of the UTRAN LTE FDD downlink and on the QoS provisioning is studied. It is described, when adopting a QoS-aware packet scheduling policy, how scheduling limitations due to control channel may affect the scheduler behavior. It is shown that the system level performance degradation could be kept negligible utilizing the dynamic link-adaptation mechanisms available on the control channel and adopting careful control channel-related design solutions. Therefore, assuming a proper dimensioning in terms of OFDM symbols reserved for control, the PDCCH could simply be modeled for LTE FDD system level simulation purposes by limiting the number of PDCCH allocations. Such a number primarily depends on the system bandwidth.

LTE-advanced systems, which aim to provide high data rate wireless services, have received world-wide researching interests nowadays. In this paper, the performance of fixed frequency reuse with different reuse factors is studied in LTE-advanced systems. Performance is measured in terms of both average cell throughput and cell edge user throughput. It is found that a properly chosen reuse factor with respect to cell size (which leads to different level of inter-cell interference), can offer up to 30% gain in average cell throughput and much higher gain for cell-edge user throughput in local area (LA). This high gain from frequency reuse makes it attractive for future LTE-advanced systems.

This paper presents a dynamic spectrum sharing algorithm to minimize the inter-cell interference, so as to achieve a high system performance. This algorithm operates in a self-organized manner without the need of any centralized control, thereby is especially useful in local area (LA) where the enhanced-NodeBs (eNB) are close and coordination among them is hard or expensive to achieve. Results show that with very limited signaling between the eNBs, the proposed algorithm can effectively improve the system performance, and it can even overcome the performance with fixed frequency plan.

This paper addresses advanced radio resource management (RRM) algorithms for multiple-input multiple-output (MIMO) transmission schemes in downlink OFDMA systems. The analysis covers the main RRM mechanisms including MIMO rank adaptation and time-frequency packet scheduling. The UTRAN Long Term Evolution (LTE) system is used as case study. System-level performance analysis is presented for 2 times 2 and 4 times 4 spatial-multiplexing, single-user MIMO transmission schemes in typical macro- and micro-cell scenarios including the effects of limited and imperfect CQI feedback from the terminals. We show that time-frequency domain RRM schemes can be successfully adapted and optimized for operations with high-rate adaptive MIMO transmission schemes.

In this paper we present the results on performance evaluation of 6-sector-site deployment and compare against 3-sector-site deployment in the downlink UTRAN LTE systems. To facilitate the performance evaluation a quasi-dynamic multicell system level simulator that follows the 3GPP UTRAN LTE specifications has been used. A significant gain in the order of 88% in site capacity is achieved by changing the 3-sector- site deployment by 6-sector-site deployment. A mixed network topology with a combination of 3 and 6-sector-site deployment has been also considered and its potential benefits investigated. The 6-sector deployment in the mixed network topology can be a viable option to meet high traffic demands in localized areas such as hot spots, yielding a capacity gain in the 6-sector sites in the order of 95 % to 110 %.

In this paper we introduce orthogonal frequency division multiple access (OFDMA) downlink general packet scheduling methods for throughput fairness control among users. The investigation is based on the 3GPP UTRAN long term evolution (LTE) and a decoupled time/frequency domain packet scheduler approach is used. It is shown that fairness can be effectively controlled with frequency domain metric weighting or time domain priority set scheduling (TD-PSS) depending on the number of users in the cell. Furthermore we introduce a principle of metric decoupling between time and frequency domain schedulers that is fundamental for maximizing throughput control. The algorithms are simulated in best effort (BE) and constant bit rate (CBR) users conditions. They are shown to provide coverage gains of up to 60% for a cell throughput loss of 5 % over the well known time-frequency domain proportional fair scheduler.

Dynamic time-frequency domain packet scheduling algorithms in the shared channel of downlink Orthogonal Frequency Division Multiple Access (OFDMA) systems have been shown to achieve high multi-user diversity scheduling gains. However, the flexibility is obtained at the cost of additional control signaling for which the availability of resources is limited. This article addresses the effects of control signaling resources limitation as well as the effects of terminal control signaling decoding errors on the performance OFDMA packet scheduling algorithms.

In this paper we analyze the downlink OFDMA system-level performances of a 2times2 dual-stream MIMO multiuser transmission scheme under the assumptions of partial and noisy channel quality indicator (CQI) feedback available from the terminals. The effects on the CQI feedback of the terminal measurement and estimation errors, quantization errors, uplink reporting format and delays are included. Two reduced CQI reporting schemes are evaluated in macro and microcell scenarios when operating in combination with a MIMO outer loop link adaptation (OLLA) and a MIMO aware frequency domain packet scheduling (FDPS) algorithm. We show that, by using OLLA and with a proper choice of the CQI reporting scheme for dual-stream MIMO, the required CQI feedback overhead can be reduced by 90% while limiting the cell throughput losses to less than 10%.

In this paper we propose a modification to Shannon capacity bound in order to facilitate accurate benchmarking of UTRAN long term evolution (LTE). The method is generally applicable to wireless communication systems, while we have used LTE air-interface technology as a case study. We introduce an adjusted Shannon capacity formula, where we take into account the system bandwidth efficiency and the SNR efficiency of LTE. Separating these issues, allows for simplified parameter extraction. We show that the bandwidth efficiency can be calculated based on system parameters, while the SNR efficiency is extracted from detailed link level studies including advanced features of MIMO and frequency domain packet scheduling (FDPS). We then use the adjusted Shannon capacity formula combined with G-factor distributions for macro and micro cell scenarios to predict LTE cell spectral efficiency (SE). Such LTE SE predictions are compared to LTE cell SE results generated by system level simulations. The results show an excellent match of less that 5-10% deviation.

In this paper, we investigate methods for improving an OFDMA system simulator in terms of trade-off between complexity and radio channel implementation accuracy. Fast fading and SINR calculations are the most resource consuming tasks of a system simulator. In order to decrease their complexity, it is proposed to reduce the number of calculated channel transfer function (CTF) realizations according to the time and frequency correlation properties of the simulated radio channel. Besides, we highlight that the upsampling of the channel impulse response (CIR), which is needed for the fast Fourier transform (FFT) application, may introduce major errors in the channel frequency statistics if it is done by simple brute force grid alignment (BFGA) method. To achieve better results we introduce a low complex upsampling method which reduces the simulation inaccuracies significantly. The possibility to trade complexity for precision is shown. It is possible for instance to divide the fast fading and SINR calculation complexity by 50 while keeping a reasonable simulation accuracy.

In this study we analyze the downlink OFDMA system level performance for three different channel quality indicator (CQI) reporting schemes. The effect of terminal measurement and estimation errors, quantization from formatting and compression, and uplink reporting delays and detection errors are included. We find that a simple threshold-based CQI scheme provides an attractive trade-off between downlink system level performance and uplink CQI signaling overhead, as compared to using a best-M scheme. When applied to the UTRAN LTE system in a 10 MHz bandwidth, we find that a frequency domain packet scheduling gain of 40% is achievable with a CQI word size of only 30-bits. Finally, the effect of applying a so-called outer loop link adaptation algorithm is reported.

In this paper we investigate the performance of frequency domain packet scheduling (FDPS) under fractional load (FL), based on the UTRAN long term evolution downlink. Under FL, the packet scheduler does not need to transmit on entire system bandwidth due to lack of traffic in the network, which leads to an improvement in the user experienced SINR. System-level simulations show that the proportional fair scheduler tries to optimize resource allocation by avoiding transmission on frequencies that are experiencing severe interference. As an example, FDPS can provide a gain of 4 dB in SINR over the round-robin scheduler, when the load is equal to 25%. The observed interference control is achieved without any centralized management. Further, FDPS under FL can provide an effective trade-off between cell throughput and coverage. The FDPS performance is dependent on the ability of link adaptation to track variations in interference. This ability is reduced when the frequency usage pattern is changing rapidly over time.

In this paper we evaluate the performance of downlink channel dependent scheduling in time and frequency domains. The investigation is based on the 3GPP UTRAN long term evolution (LTE) parameters. A scheduler framework is developed encompassing frequency domain packet scheduling, HARQ management and inter-user fairness control. It is shown that by dividing the packet scheduler into a time-domain and a frequency-domain part the fairness between users can be effectively controlled. Different algorithms are applied in each scheduler part, and the combined performance is evaluated in terms of cell throughput, coverage, and capacity. We show that frequency-domain packet scheduling can provide a gain of around 35% in both throughput and coverage over opportunistic time-domain only scheduling. Furthermore, it is shown that by using an equal throughput scheduler, coverage can be improved by 100% at the expense of a 5% loss in average cell throughput in comparison with the proportional fair scheduler.

This paper presents HSDPA performance evaluation in an urban micro cell environment with outdoor base station antenna heights below roof-top level (10 m) and both outdoor and indoor pedestrian mobiles (3 km/h). A path loss model which accounts for the 3D geometry of the radio environment is used, thus allowing the simulation of indoor user locations at different building floor levels. The single user throughput evaluation is carried out using realistic HSDPA link-level simulations combined with the newly obtained statistics of the geometry factor in the considered micro cell environment. The results with 80% HSDPA power and 15 HS-PDSCH multi-codes showed median single-user throughput in the range of 4.8 Mbps/cell. It was also found that ground floor areas can be served with up to 5% better median throughputs compared to the outdoor and high (top) floor areas

Accurate positioning of wireless devices using short-range link-technologies is interesting for a number of applications including tracking, location-based services, and context sensitive networking. In this paper, accuracy and timing aspects for an indoor positioning method based on triangulation using signal strength measurements of Bluetooth links are analyzed experimentally and via simulation models. In the approach chosen in this paper, the delay to obtain signal strength measurements is determined by complex interactions of the Bluetooth inquiry procedure, which are analyzed in detailed simulation experiments. The location accuracy analysis is performed experimentally for the setting of an indoor corridor scenario including multi-path propagation properties

This paper describes radio channel and BER investigations performed in various scenarios typical to the TETRA direct mode operation (DMO), in a forest area. The data from radio channel sounding measurements was analysed in terms of average fade duration and envelop CDF. The same data was used to evaluate the unprotected BER on a TETRA communication link. The BER level distribution was compared to the distribution obtained when simulating a pedestrian speed TETRA DMO radio channel. The dynamics of the mobiles can have a strong influence on the radio link quality. As a general tendency, higher practical BER values can be expected as compared to the simulations when using the simple TETRA radio channel model.