Emerging domains such as wireless industrial control, vehicular communications, smart grids, and augmented reality demand low latency, high throughput, and high reliability from wireless communication systems. Unfortunately, single connectivity (SC) communications frequently fail to fulfill these stringent requirements. To address these challenges, employing a multi-connectivity (MC) solution appears to be a promising technique. In this paper, in the context of Horizon Europe COMMECT project, we seek to develop a multi-connectivity solution that intelligently integrates cellular and satellite networks for the purpose of monitoring livestock transport in rural regions where 5G coverage is limited. Multi-connectivity can be helpful for meeting EU regulations requiring seamless communication between transport units and the operational center to ensure animal welfare during transit. To achieve this, we employ machine learning (ML) models within a Classification and Regression framework in the proposed muti-connectivity solution. The ML models process radio-related key performance indicators (KPIs) as inputs to estimate network throughput and latency. The outputs of the model are used to decide whether to continue with the cellular link or activate the backup satellite link in the multi-connectivity setup, ensuring an almost uninterrupted connection. This capability is particularly crucial in regions where 5G coverage is limited, and maintaining a reliable connection is essential. To evaluate the proposed framework, we used a hybrid emulation setup based on experimental data collected in the northern part of Denmark. The emulation results demonstrate that the MC solution significantly outperforms the cellular SC. Although our solution is designed for livestock transport monitoring, it can be adapted for other applications, such as precision farming, in areas with insufficient 5G availability.

Low power, long range, wireless communication technologies enable a range of monitoring applications in difficult to reach locations. In this paper, we investigate one such application for monitoring an underground pipeline infrastructure in the 868MHz Industrial, Scientific and Medical (ISM) band. We deployed five underground LoRa/LoRaWAN communication modules on district heating pipes, sealed off below an asphalted road segment. Several specific measurements have been conducted to characterize the propagation conditions from below to above ground, and from which we propose models decomposing propagation into separate contributions from soil, ground to free-space, and above ground propagation. The main novelty of the work lies in the application to covered surfaces and the combined above ground/aerial model framework for communication from below ground. It was found that the Peplinski soil loss model is applicable for estimating the effect of the ground, which in combination with Fresnel refraction and a log-distance model for above ground propagation leads to a consistent modeling framework for propagation to lamp post height gateway infrastructure. For aerial-based gateways, the main finding is that the propagation from below to above ground changes the propagation behavior with distance above ground, despite the otherwise unobstructed free space propagation path. This led to a path loss model with loss increasing exponentially with height and according to cylindrical wave propagation with lateral (2D) distance, aligning with the estimations based on the ground-based model. The results suggest overall that the volumetric water content (VWC) of a compacted and covered soil mixture tends to stabilize to high values.

Accurate prediction of network key performance indicators (KPIs), such as throughput and latency, is important for maintaining Quality of Service (QoS) and enabling intelligent, proactive optimization in mobile applications to support reliable and ubiquitous connectivity. One application is the monitoring of livestock transport, a key focus of the Horizon Europe project COMMECT, which aims to develop a smart multi-connectivity solution to ensure seamless connectivity throughout the transport route. Although beneficial, predicting network KPIs based on radio KPIs is particularly challenging in dynamic environments due to the intricate nature of their relationship. In our previous study, this weak relationship led to limited performance in applying a supervised Random Forest (RF) model. Aiming to improve the prediction of network KPIs, we investigate the convolutional neural network-long short-term memory (CNN-LSTM) time-series model, which combines convolutional layers for spatial feature extraction with LSTM layers to learn temporal dependencies. Unlike the supervised RF model, the current approach predicts network KPIs based on past information about the network KPI itself, bypassing the need for a mapping between radio and network KPIs. In our comparison, the CNN-LSTM time series and RF models have been trained and tested based on measured 5G throughput and latency data collected in northern Denmark. The CNN-LSTM model outperforms the RF model, achieving an R2score improvement of 26.17% for latency and 15.81% for throughput, highlighting its ability to adapt to varying network conditions in a realistic setting.

Long-range Wide-area Network (LoRaWAN) is an innovative and prominent communication protocol in the domain of Low-power Wide-area Networks (LPWAN), known for its ability to provide long-range communication with low energy consumption. However, the practical implementation of the LoRaWAN protocol, operating at the Medium Access Control layer and specially built to work upon the LoRa physical layer, presents numerous research challenges, including network congestion, interference, optimal resource allocation, collisions, scalability, and security. To mitigate these challenges effectively, the adoption of cutting-edge data-driven technologies such as Deep Learning (DL) and Machine Learning (ML) emerges as a promising approach. Interestingly, very few existing surveys or tutorials have addressed the importance of ML- or DL-based techniques for LoRaWAN. This article provides a comprehensive survey of current LoRaWAN challenges and recent solutions, particularly using DL and ML algorithms. The primary objective of this survey is to stimulate further research efforts to enhance the performance of LoRa networks and facilitate their practical deployments. We begin by emphasizing the characteristics of LoRaWAN compared to other LPWAN technologies and then examine the technical specifications of LoRaWAN that have been released so far, as well as the current research trends. Furthermore, we discuss an overview of the most utilized DL and ML algorithms for overcoming LoRaWAN challenges. We also present an interoperable reference architecture for LoRaWAN and validate its effectiveness using a wide range of applications. Additionally, we shed light on several evolving challenges of LoRa and LoRaWAN for the future digital network, along with possible solutions. Finally, we conclude our discussion by briefly summarizing our work.

Wi-Fi is one of the WLANs technologies with the highest penetration in society worldwide. In recent years, Wi-Fi 6E has been defined, which uses the 6 GHz band with higher bandwidth and resource availability. However, the range for this band decreases due to the increase in frequency compared to 2.4 GHz and 5 GHz bands, hence the proposal for the use of mesh networks to overcome the limited range. Therefore, this work empirically assesses the network performance through different setups in indoor scenarios to determine the optimal placement of extender nodes in a Wi-Fi 6E mesh network. The experimental methodology follows a dual approach, studying the channel propagation conditions in the 6 GHz band versus 2.4 GHz and 5 GHz, as well as the throughput reported through connectivity with Wi-Fi 6E. The results quantitatively show the reduction in effective network range in the 6 GHz band, due to the increase in frequency, and its influence on effects such as blocking or around-corner propagation. Based on this analysis, a set of guidelines is developed for positioning the extender nodes in the network to maximize network performance according to the propagation channel conditions.

This paper investigates the possibility of using satellite connectivity via Starlink for achieving full digital inclusion in areas where traditional mobile or fixed-broadband are not cost-effective options due to low population density. The evaluation is based on experimental data and focuses on Starlink’s performance in terms of throughput, specifically assessing its potential to meet the target of 100 Mbps downlink (DL) and 30 Mbps uplink (UL) speeds established by the Danish government for a full digital inclusion of households located in under-served areas. The experimental results indicate that the UL target is the limiting factor, even when a single user is active within the coverage area of a satellite beam. We observe that the UL and DL maximum throughput divide in equal proportion to the number of active users and the maximum (single-user) throughput of approximately 400 Mbps DL and 21 Mbps UL, the latter limited by UL link budget. Based on these numbers, and further assumptions, we analyse to what extent Starlink can provide a satisfactory broadband service to the approximately 20.000 households not meeting the Danish broadband targets by 2025. Whereas the targets cannot be met in a strict sense, we estimate that Starlink can provide satisfactory broadband service to approximately 4000 households across Denmark with experienced data rates of 60-100 Mbps DL and 5-10 Mbps UL, which, if households are selected out of the ones having the otherwise lowest speeds by 2025, corresponds to a significantly improved broadband experience. In the region with the lowest population density this amounts to 42% of households in the group not fulfilling the targets by 2025, and opposite, in the Capital region 4-5%.

Swarm production robots, an enabler for Industry 4.0, are expected to establish direct communication links with each other based on proximity. The 3rdGeneration Partnership Project (3GPP)'s New Radio sidelink is a candidate technology to enable such communication links. However, when operating in autonomous resource selection mode (mode 2), sidelink communications are prone to half-duplex and interference problems, the severity of which increases with the swarm's density. In this paper, we study how beam selection using directional antennas and context information can help reduce the impact of these problems and thus improve the reliability of packet reception. We evaluate the effect of directional antennas when applied at the transmitter and receiver, both separately and simultaneously, for increasing swarm density. Our evaluations show that these enhancements let mode 2 achieve 120% more user equipments (UE) in the swarm for a 99.99% reliability target, compared to the case where these enhancements are not applied.

In the context of the Horizon Europe COMMECT project, we seek to develop a multi-connectivity solution that intelligently integrates cellular and satellite networks for the purpose of monitoring livestock transport in rural regions, where 5G coverage is limited. To achieve seamless connection in the multi-connectivity solution, we use machine learning (ML) based on a Random Forest (RF) classifier to efficiently integrate 5G and satellite links. The binary output of the classifier is used to activate the satellite link, in addition to the cellular link, to ensure uninterrupted connection according to the targeted performance criteria, often necessary in rural areas with limited 5G coverage. The input to the ML model are radio-related key performance indicators (KPIs). In our emulation, using experimental data, we demonstrate that our proposed solution fulfills the seamless connectivity requirements of the COMMECT project in most cases through the combined utilization of cellular networks and satellite links. This is achievable because the RF classifier, based on pre-processed radio KPIs, can accurately predict when the cellular network is unable to provide satisfactory service with a success rate of 94.3 %. The proposed solution achieves the level of application throughput required to support monitoring of livestock transport, thereby advancing communication systems for various scenarios of limited 5G connectivity.

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.

Decentralized cooperative resource allocation schemes for robotic swarms represents an alternative to infrastructure-based communications across different commercial, industrial and environmental protection use cases. The cooperative communication schemes, device sequential and group scheduling in [1], have shown superior performance in comparison to 5G NR sidelink mode 2, but have also shown performance issues due to signaling overhead and signaling induced failures. In this paper we introduce different techniques that reduce the failure probability of data packet transmissions and the packet inter-reception (PIR) time. We evaluate two techniques, respectively, of incremental redundancy using hybrid automatic repeat request and link adaptation by aggregation, as well as their combination for our decentralized cooperative resource allocation schemes and sidelink mode 2. Our results show that the introduced enhancements, allow to double the amount of supported swarm members while achieving four nines reliability when compared to the case where the same enhancements are applied to the sidelink mode 2.

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.

Robotic swarms are becoming relevant across different industries. In an indoor factory, collective perception of the environment can be used for increased factory automatization. It requires reliable, high throughput and low latency communication of broadcasted video data among robots within proximity. We introduce two new decentralized resource allocation schemes that meet these stringent requirements. The two proposed decentralized schemes are denoted as: (i) device sequential, where robots take turns to allocate resources, and (ii) group scheduling, where robots select local group leaders who perform the resource allocation. A comparative evaluation is performed by simulation against a centralized resource allocation scheme and the current 3GPP release 16 NR sidelink mode 2 scheme. Our results show that the two proposed decentralized resource allocation schemes outperform sidelink mode 2 due to the mitigation of the half-duplex problem. The proposed schemes reach the throughput target of 10 Mbps with a reliability of 99.99% for a swarm size of 50 robots.

In this paper, we analyse received signal strength data from large-scale field trials, simulating realistic user behavior during a disaster event in build-up areas. Based on a simple framework, we identify the overall behavior of the link loss versus distance, as well as the characteristics of random local variability in the link loss. Particularly, we analyse the cross-correlation in the random variation between pairs of links, in dependence of the separation angle between them. Given the extent of the data set, we believe the findings have statistical significance and can be used as a reference for calibrating models in simulation of mesh network performance. To this end, we discuss the main contributing effects to link loss variability, including environment and body loss shadowing.

As in other vertical markets, wireless communications are expected to play a fundamental role in the digitalization of the mining industry. Akin to most industrial applications, careful and scenario specific understanding of the radio propagation conditions is key to plan and deploy a reliable wireless network. However, surface mining presents an additional challenge when compared to other industrial scenarios: inherent large-scale topographic variability. Therefore, it is necessary to validate if the radio propagation models remain accurate over large topographic change. In this work, we summarize and compare the results collected in two distinct measurement campaigns, with the predictions of a dedicated path loss model (Vale Model) previously derived from measurements in surface mines. The second measurement campaign is performed by means of an automated site survey, that takes advantage of operational wireless systems and mining equipment to collect data samples. The results show that even with different transmit frequencies, topographic variation, test equipment, and measurement methods (dedicated versus automated site surveys), the Vale model provides a good fit for path loss prediction in open-pit mines, with RMSE values in the order of 7 dB. Besides, this is the first time a radio propagation model has been validated over large topographic changes in a surface mining scenario.

The mining industry is on a transition towards unmanned operations. This implies a step change in wireless infrastructure expansion to support autonomous and teleoperated machinery. This paper investigates how the topographic changes over the course of 10 years of continuous mining affect the propagation conditions, and impacts the performance associated with different deployment strategies for wireless networks in a large open-pit mining complex in Brazil. Through a series of system-level simulations, using detailed terrain models, realistic traffic volumes and a dedicated propagation model, we compare the ability of different deployment strategies, and network features, to meet given performance targets with existing technology. The results show that heterogeneous deployments can be exploited to continuously guarantee coverage in this ever- changing topography, while interference mitigation techniques, such as enhanced inter-cell interference coordination (eICIC) and beamforming, can be used to reduce the system outage without need to increase the spectrum.

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.

This paper presents the results of wireless channel measurement campaign in the 3 GHz to 8 GHz frequency range. The measurements were performed with focus on the short-range with a transmitter-receiver separation distance less than 9 m in two typical industrial environments: a low clutter density manufacturing space, and a high clutter density one. We analyzed the statistical properties of the most important temporal and large-scale propagation characteristics including total received energy, path loss exponent, maximum excess delay (MED) and root mean square (RMS) delay spread based on the measurements. Statistical models for the RMS delay spread and MED are also presented using the log-normal and Gamma distributions.

In this paper, we investigate the suitability of the propagation models ITU-R 526, Okumura Hata, COST Hata models and Standard Propagation Model (SPM) to predict the path loss in open-pit mines. The models are evaluated by comparing the predicted data with measurements obtained in two operational iron-ore mining complexes in Brazil. Additionally, a simple deterministic model, based on the inclusion of an effective antenna height term to the ITU-R 526, is proposed and compared to the other methods. The results show that the proposed model results in root-mean-square error (RMSE) values between 5.5 dB and 9.2 dB, and it is capable of providing a close approximation of the best predictions (i.e. those with lowest RMSE) as provided by the SPM. The proposed model, however, reduces the calibration complexity considerably.

One of the 5G use cases, known as ultra- reliable communication (URC), is expected to support very low packet error rate on the order of $10^{-5}$ with a 1 ms latency. In an industrial scenario, this would make possible replacing wired connections with wireless for controlling critical processes. Industrial environments with large metallic machinery and concrete structures can lead to deep shadowing and severe fading in the radio propagation channel, and thus pose a challenge for achieving the outage levels in connection with URC. In this paper, we present and analyze the large-scale propagation characteristics of two different industrial environments - open production space and dense factory clutter - based on measurements conducted at 2.3 and 5.7 GHz. By including a large number of spatially distributed samples, as per our experimental approach, we show the importance of properly characterizing the large-scale fading outage for URC. For instance, we show that based on a simple one-slope distance dependent path loss model, the conventional log-normal model for large-scale shadow fading is by far too simple for this environment. Our results show that at the 10^{-4} percentile, the tail of the shadow fading distribution can deviate by up to 10-20 dB from the log-normal model with respect to the average NLOS values (around 6 dB and 8 dB at 2.3 and 5.7 GHz, respectively). The simplicity of the one-slope path loss model, and its ability as we show, to express the trends with respect to scenarios, frequencies, and antenna heights, makes it an attractable option. However, there is a need for further experimental insight, possibly in combination with deterministic analysis, to get a better understanding of the large-scale fading for the study of URC in industrial environments.

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.

In this paper we present the results of an extensive measurement campaign performed at two large iron ore mining centers in Brazil at the 2.6 GHz band. Although several studies focusing on radio propagation in underground mines have been published, measurement data and careful analyses for open-pit mines are still scarce. Our results aim at filling this gap in the literature. The research is motivated by the ongoing mine automation initiatives, where connectivity becomes critical. This paper presents the first set of results comprising measurements under a gamut of propagation conditions. A second paper detailing sub-GHz propagation is also in preparation. The results indicate that conventional wisdom is wrong, in other words, radio-frequency (RF) propagation in surface mines can be far more elaborate than plain free-space line-of-sight conditions. Additionally, the old mining adage “no two mines alike” seems to remain true in the RF domain.

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.

Unique Word Discrete Fourier Transform -spread - Orthogonal Frequency Division Multiplexing (UW DFT-s-OFDM) waveform replaces the Cyclic Prefix (CP) with a known sequence which is contained in the symbol itself rather than being appended to it. In this paper, we propose a new UW DFT-s-OFDM design which aims at exploiting such known sequence at the tail of the signal for tracking the variations of the radio channels on a symbol basis, thus overcoming the limited flexibility of DFT-s-OFDM waveforms in multiplexing reference sequences and data. Further, we also present a criterion for efficiently selecting the reference sequences to be adopted by users experiencing fast time-varying channel conditions. Initial simulation results show the capability of the proposed design of improving the link performance of high speed users, even without additional overhead.

Full duplex transmission is envisioned as one of the potential breakthrough for a 5th Generation (5G) radio access technology. In this paper, we evaluate the performance of full duplex transmission in a network of dense small cells by using real channel measurements. A large measurement campaign is carried out in an indoor office and an open hall scenario, and such measurements are then fed to a system level simulator for offline analysis. Cell throughput results show that the promised 100% performance gain of full duplex over traditional half duplex transmission is significantly jeopardized by the increase of the intercell interference due to the simultaneous transmission and reception, and is further reduced in case of low cell activity factor.

The share of mobile User Equipments (UEs) supporting insertion of Multiple Subscriber Identity Modules (Multi-SIM) has increased significantly throughout the world. Due to cost optimization, Multi-SIM UEs are often designed such that they discard chunks of data in one subscriptions active data stream in order to support network communication for another subscription, due to radio hardware or software access conflicts. Limited signalling between the UE and Base Station (BS) makes it such that the UE has no way to signal that it is a Multi-SIM UE, or that it will discard data. We present an algorithm based on Markov chains which is able to blindly detect if a connected UE is a Multi-SIM UE and predict potential data loss. During operation, the state and transition models used in the algorithm are continuously updated in order to let the algorithm adapt to the pattern of discarded data in the active connection. The algorithm is investigated within the KPIs of; number of correct detections made, number of missed gaps, and number of false predictions. The analysis is created using a link level simulator and the presented results show that the algorithm is able to detect and predict Multi-SIM gaps, and as the algorithm learns it adapts the prediction to the actual operations of the UE.

User Equipments (UEs) which support simultaneous activity from Multiple Active Subscriber Identities (Multi-SIM) has gained popularity within the last years. Such UEs are forced to discard data on one of the SIMs when both try to access the Radio Frequency (RF) interface simultaneously, creating gaps in the data transfer. The discarded data due to Multi-SIM gaps, along with channel errors, significantly increase the probability of high latency data subframes. High latency increases the probability of data subframes being discarded. In this paper we present an algorithm with which it is possible to decrease the probability of discarded data subframes due to high latency. The algorithm takes advantage of the fact that the connections of each SIMs are unaligned and therefore gaps will only cover some timeslots partially. In such a case, it is possible to recover data using existing error correction coding, if the amount of corrupted bits corresponds to the error correction capability of the code. We investigate the performance of the algorithm using a link level simulator in respect to KPIs; overall throughput, decrease in subframe loss probability, and block error rate. The algorithm is tested in three different radio conditions as they comprise different restrictions to the algorithm. We show how the algorithm significantly decreases the subframe loss probability due to Multi-SIM, without significant impact on the overall throughput.

User Equipments (UEs) supporting insertion of Multiple Subscriber identity Modules (Multi-SIM) have been becoming increasingly popular within the last half decade. End-user requires low cost, which is achieved by implementing a minimum of extra hardware resources compared to a single Subscriber Identity Module (SIM) UE. This sparse amount of extra hardware give rise to access conflicts between the multiple connections and the available hardware, ending up in lost data on at least one of the connections. This paper suggests framework with a dynamic weighting system used to resolve such conflicts, using data characteristics. The goal of the weighting is to handle conflicts optimally; i.e. each connections procedure has minimal impact on the others. We present the framework, as well as the dynamic weighting routine. Throughout the paper we present performance results, showing that the proposed method significantly reduces the latency experienced by the active data connection, when under the influence of Multi-SIM conflicts. The results are obtained using a Long Term Evolution (LTE) downlink simulator combined with a Global System for Mobile (GSM) control channel simulator. Furthermore, we also analyse the impact on the conflicting idle mode SIM.

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.

The number of User Equipments (UEs) with multiple active subscriber identities (Multi-SIM) will increase throughout the coming years. The requirement in such UEs for each of the Subscriber Identity Modules (SIMs) to have parallel network access, invoke access conflicts on baseband/RF level. These conflicts ends up in one or more of the inserted SIMs being denied access for brief period of time, usually on the scale of tenths of milliseconds repeated every half to two minutes. These Multi-SIM conflicts are analysed using a combination of link level, and frame based simulation. The simulation clarifies the impact of Global System for Mobile (GSM)-like idle mode operations conflicting with an active Long Term Evolution (LTE) connection. The presented results show the effect Multi-SIM has on Radio Link Control (RLC) Unacknowledged Mode (UM) Service Data Unit (SDU) drop rate, and Acknowledge Mode (AM) SDU arrival time. It is shown that the impact of Multi-SIM on the drop rate and arrival time of the SDUs is based not only on the amount of conflicts between the SIMs, but also on the time alignment between the basestations retransmission timing strategy and the placement of the conflicts in time. The results may prove as base for discussions on some requirements to the basestations network configuration and performance.

The 5G vision of 10 Gb/s leads to performance and power consumption challenges in the mobile terminal receiver because 10 Gb/s requires 400 MHz bandwidth, faster baseband processing, and an increased number of component carriers and MIMO streams. The contribution of this paper is to estimate the impact from these physical layer requirements to the power consumption of main receiver components, including LNA, ADC and baseband processor with Turbo decoding, in a Direct Conversion Architecture. The estimate of power consumption results from a comprehensive survey of component performance evolution, and extrapolation hereof to estimate trends, and main challenges, towards 2030. According to our results, in 2020 the receiver power consumption exceeds 3 W, and is thus a challenge to be addressed. Assuming the performance evolution continues as observed in this work, the 5G receiver will be on par with the current LTE implementations in 2027 and thus consume less than 0.8 W.

Continuous optimization of Mobile Broadband Networks (MBNs) is done to simultaneously optimize and balance some performance factors such as Quality of Service (QoS) and energy usage. Initial MBN optimization approaches used various heuristics, while more advanced approaches have investigated the MBN optimization potential using predictions of future node loads based on historical load data. However, using only historical load data for prediction often fails when events occur. This paper presents MOST (Mobile broadband network Optimization using planned Spatio-Temporal events) approach that additionally uses external spatio-temporal information about planned events, e.g., the time and place of big concerts or football matches, to improve the prediction quality, thus enabling more correct MBN optimization. A simulation using experimental data from a mobile broadband network in Denmark shows that MOST is able to improve the prediction quality very significantly, and thus enables significantly better MBN optimizations to be performed.

Advanced receivers are a key component of the 5th Generation (5G) ultra-dense small cells concept given their capability of efficiently dealing with the ever-increasing problem of inter-cell interference. In this paper, we evaluate the potential of interference suppression receivers in real network scenarios using a software defined radio (SDR) testbed. The experimentation is carried out in an indoor office and open hall scenarios. In particular, we study to what extent the interference suppression receiver is an alternative to traditional frequency reuse techniques. To this end we evaluate the Interference Rejection Combining (IRC) and Successive Interference Cancellation (SIC) receivers and different rank adaptation approaches. Each node in our software defined radio (SDR) testbed features a 2×2 MIMO transceiver built with the USRP N200 hardware by Ettus Research. Our experimental results confirm that interference suppression receivers can be a valid alternative to frequency reuse, by achieving nearly the same outage and higher peak throughput performance.

Inter-cell interference is the main performance limiting factor in the dense deployment of small cells targeted by the upcoming 5th Generation (5G) radio access technology. In this paper, we present an experimental evaluation of inter-cell interference mitigation techniques in a real indoor office deployment with four cells, where each cell features one Access Point (AP) and one User Equipment (UE). In particular, we compare traditional Frequency Reuse Planning (FRP) with the recently proposed Maximum Rank Planning (MRP) technique, which relies on the degrees of freedom offered by the multi-antenna transceivers for suppressing a number of interfering streams. Different receiver types are also considered, namely Interference Rejection Combining (IRC) and the interference unaware Maximum Ratio Combining (MRC). Each node in our software defined radio (SDR) testbed features a 2 x 2 MIMO transceiver built with the USRP N200 hardware by Ettus Research. The experimental results in a fully loaded network reveal the capability of the MRP technique to achieve higher throughput performance than FRP for 90% of the cases when IRC receivers are used. Lower network loads lead to further performance improvements for MRP.

The Interference Rejection Combining (IRC) receiver can significantly boost the network throughput in scenarios characterized by dense uncoordinated deployment of small cells, as targeted by future 5th generation (5G) radio access technology. This paper presents an experimental study on the potential benefit of IRC receiver in real deployment scenarios. The study is carried out using a software defined radio (SDR) testbed network with four cells, each featuring one Access Point (AP) and one User Equipment (UE) with two antennas. The testbed network was placed in an indoor office and open hall scenarios, respectively. In each scenario, the cells were arranged to characterize the propagation in different spatial configurations. Using the obtained propagation data, we analysed the cases of closed and open subscriber group for the respective scenarios, to compare the achievable throughput with IRC and Maximum Ratio Combining (MRC) receivers. Different frequency reuse schemes were also considered. The throughput results confirm the effectiveness of the IRC receiver in improving the network throughput with respect to the MRC receiver, under the assumption of single stream (rank 1) transmission. Results show average gains up to around 40% and outage gains up to 70% over the MRC receiver. The combination of the IRC receiver and frequency reuse achieves a favourable trade-off between the network throughput and fairness. Overall, due to the direct propagation, the open hall open subscriber group scenario is benefiting the most from the ability of the IRC receiver to cancel a strong dominant interferer.

Zero-tail Discrete Fourier Transform -spread OFDM (ZT DFT-s-OFDM) modulation allows to dynamically cope with the delay spread of the multipath channel, thus avoiding the limitations of hard-coded Cyclic Prefix (CP). In this paper, we discuss the potential of ZT DFT-s-OFDM modulation for the envisioned 5th generation (5G) radio access technology, characterized by an ultra-dense deployment of small cells and the support of novel paradigms such as Device-to-Device (D2D). We address the benefits of ZT DFT-s-OFDM in terms of coexistence among devices operating over adjacent frequency chunks, possibility of adopting unified radio numerology among different cells, reduced latency and support of agile link direction switching. The robustness of ZT DFT-s-OFDM towards non-idealities such as phase noise and non-linear power amplifier is also discussed.

Time synchronization in a large network of small cells enables efficient interference management as well as advanced transmission techniques which can boost the network throughput. In this paper, we focus on the distributed initial synchronization problem and propose different solutions aiming at reducing the residual asynchronous interference while limiting the number of large timing reconfigurations at each node. Simulation results show the effectiveness of an ID-based approach in limiting the asynchronous interference, however at the expense of a potential high number of timing reconfigurations. A pathlossbased solution limits such reconfigurations but also leads to a higher residual interference than the ID-based solution. An hybrid solution is shown to be an effective trade-off between the two former approaches.

Research on fifth generation (5G) radio access technology (RAT) is ramping up, with the goal of significantly improving user data rates and latency compared to previous RAT generations. While energy efficiency (EE) of the user equipment (UE) was not a key optimization parameter for the current wireless standards, it is anticipated to become a distinguishing factor for 5G. In this paper, we analyze established and emerging technological solutions for features such as waveform, frame structure, duplexing and multiple antenna transmission from an EE perspective. Our contribution is to identify and discuss the features' pros and cons in achieving high performance in terms of data rate and/or latency while limiting their effect on the UE power consumption. Based on the discussion we give general recommendations for an energy efficient 5G design in the context of a previously proposed RAT concept.

Energy-efficient buildings are gaining momentum in order to comply with the new energy regulations. Especially in northern cold countries, thick reinforced walls and energy-efficient windows composed of several layers of glass plus metal coating are becoming the de facto elements in modern building constructions, and it has been noticed that they can impact heavily on radio signal propagation. This paper presents a measurement-based analysis of the outdoor-to-indoor attenuation experienced in several modern constructions compared to an old building. The measurements are performed for frequencies from 800 MHz to 18 GHz with the aim of identifying the frequency dependence and the impact of the new materials on not only the cellular frequency bands used today (mainly below 3 GHz), but also the potential future bands (above 3 GHz). The results show a material dependent and a frequency dependent attenuation, with an average increase of 20-25 dB in modern constructions compared to the old construction, which presents a low and almost constant attenuation below 10 dB. The different measurement results and observations presented along the paper are useful for future radio network planning considerations.

In real urban deployments, base station antennas are typically not placed in free space conditions. Therefore, the radiation pattern can be affected by mounting structures and nearby obstacles located in the proximity of the antenna (near-field), which are often not taken into consideration. Also the intrinsic propagation mechanisms of the urban environment (far-field) can contribute to the distortion of the radiation pattern observed in a practical deployment scenario, especially when comparing it to the antenna pattern provided by the manufacturer and typically measured in free space. This paper presents a combination of near-field and far-field simulations aimed to provide an overview of the distortion experienced by the base station antenna pattern in two different urban deployment scenarios: rooftop and telecommunications tower. The study illustrates how, in comparison with the near-field effects, the urban propagation becomes the main contributor to the total distortion experienced. For the considered scenarios, the simulation results show a front-to-back-ratio reduction of approximately 10-15 dB in the effective antenna pattern compared to the free space reference. The near-field distortion has been evaluated by means of finite integration technique (FIT) simulations, while the far-field effects have been analyzed through intelligent ray tracing (IRT).

The usage of Minimum Mean Square Error - Interference Rejection Combining (MMSE-IRC) receivers is expected to be a significant performance booster in the ultra-dense deployment of small cells envisioned by an upcoming 5th generation (5G) Radio Access Technology (RAT). However, hardware limitations of the radio- frequency front-end and poor covariance matrix estimation may severely compromise its ideal gains. In this paper, we evaluate the network performance of MMSE-IRC receivers by including the effects of the receiver imperfections as well as realistic covariance matrix estimates. System level simulation results confirm that a realistic MMSE-IRC receiver can achieve throughput gains close to ideal, provided a reasonably high resolution Analog-to-Digital Converter (ADC) as well as a supportive radio frame format design are used.

The characteristics of the deployment scenario are fundamental elements in the performance evaluation of wireless networks inter-cell interference coordination (ICIC) schemes. The statistical validation of such concepts is typically achieved by means of system-level simulation campaigns where regular reference scenarios and stochastic channel models are employed. It is an important next step to verify that the trends observed in the reference scenarios compare equally well in more practical deployments. For such comparison, it is required to evaluate an extensive set of link conditions, reflecting the many possible configurations that can be experienced in a practical scenario. In this paper we adopt an experimental procedure, using a software defined radio testbed, for acquiring almost 1000 different radio link conditions between the nodes of a relevant wireless indoor network scenario. The acquired measurements, were used as input to a system level simulator in order to evaluate the performance of a local area decentralized ICIC scheme. The obtained performance results highlight the contribution of the selected scheme and provide a new insight for the validation of the related simulation-based studies, previously published in literature.

The 3.5 GHz band is a strong candidate for future urban micro cell deployment with base station antennas located below rooftop. Compared to other frequency bands, propagation in the 3.5 GHz band is relatively unexplored for the micro cell deployment. This paper presents a measurement-based analysis of outdoor and outdoor-to-indoor propagation at 3.5 GHz in comparison to the more well-known frequency of 1.9 GHz. A simple two-slope line-of-sight/non-line-of-sight outdoor path loss model is proposed and compared to different existing path loss models. The outdoor path loss is found to be approximately 5 dB higher for 3.5 GHz compared to 1.9 GHz. The outdoor-to-indoor propagation is investigated for two office buildings and different street shops. For the different presented scenarios, penetration loss increases with frequency and is found to be up to 5 dB higher for 3.5 GHz compared with 1.9 GHz. Although some existing models predict the observations with good accuracy, we propose a model based on line-of-sight probability that is simpler and easier to apply.

Despite being a simple and commonly-applied radio optimization technique, the impact on practical network performance from base station antenna downtilt is not well understood. Most published studies based on empirical path loss models report tilt angles and performance gains that are far higher than practical experience suggests. We motivate in this paper, based on a practical LTE scenario, that the discrepancy partly lies in the path loss model, and shows that a more detailed semi-deterministic model leads to both lower gains in terms of SINR, outage probability and downlink throughput and lower optimum tilt settings. Furthermore, we show that a simple geometrically based tilt optimization algorithm can outperform other tilt profiles, including the setting applied by the cellular operator in the specific case. In general, the network performance is not highly sensitive to the tilt settings, including the use of electrical and/or mechanical antenna downtilt, and therefore it is possible to find multiple optimum tilt profiles in a practical case. A broader implication of this study is that care must be taken when using the 3GPP model to evaluate advanced adaptive antenna techniques, especially those operating in the elevation dimension.

Facing the huge success of mobile devices, network providers ceaselessly deploy new nodes (cells) to always guarantee a high quality of service. Nevertheless, keeping turned on all the nodes when traffic is low is energy inefficient. This has led to investigations on the possibility to turn off network nodes, fully or partly, in low traffic loads. To accomplish such a dynamic network optimization, it is crucial to predict very accurately low traffic periods. In this paper, we tackle this problem using data mining and propose Spatio-Temporal Ensemble Prediction(STEP). In a nutshell, STEP is based on the following two main ideas: (1) since traffic shows very different behaviors depending on both the temporal and the spatial contexts, several prediction models are built to fit these characteristics; (2) we propose an ensemble prediction technique that accurately predicts low traffic periods. We empirically show on a real dataset that our approach outperforms standard methods on the low traffic prediction task.

Beyond 4th Generation (B4G) local area networks will be characterized by the dense uncoordinated deployment of small cells. This paper shows that inter-cell interference, which is a main limiting factor in such networks, can be effectively contained using Interference Rejection Combining (IRC). By simulation we investigate two significantly different interference scenarios with dense small cell deployment. The results show that IRC brings considerable improvement in outage as well as in peak and median throughputs in both scenarios, and thus has a big potential as a capacity and coverage enhancing technique for B4G. The IRC gain mechanism depends strongly on the interference scenario and to some extent on the use of frequency reuse. These results are achieved with no coordination between cells and suggests that MIMO rank adaptation and IRC can be done independently.

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.

In this work a novel LTE user equipment (UE) power consumption model is presented. It was developed for LTE system level optimization, because it is important to understand how network settings like scheduling of resources and transmit power control affect the UE's battery life. The proposed model is based on a review of the major power consuming parts in an LTE UE radio modem. The model includes functions of UL and DL power and data rate. Measurements on a commercial LTE USB dongle were used to assign realistic power consumption values to each model parameter. Verification measurements on the dongle show that the model results in an average error of 2.6 %. The measurements show that UL transmit power and DL data rate determines the overall power consumption, while UL data rate and DL receive power have smaller impact.

As small cell solutions for efficient in-building wireless deployment, the distributed antenna system (DAS) and Femtocells constitute two major options. In this work, we study the Total Cost of Ownership (TCO) in combination with system performance in order to reach technology-economical conclusions regarding of these deployment options. Our aim is to identify the most cost economical solution for indoor wireless deployment which meets the indoor capacity need and provides ubiquitous indoor coverage. In the analysis we focus on LTE enhancement in the enterprise buildings. We discuss the unique cost features of DAS and Femto systems and highlight the importance of backhaul visibility in the cost analysis. For enterprise building solutions, we show the cost advantage of low-cost Femtocells over DAS in all scenarios regardless of coverage building size. We also suggest when DAS becomes more economical for large buildings with low data traffic need.

Relay base stations are expected to play an important role in extending coverage for beyond 3G networks, such as LTE-A. However, the signal quality experienced on the backhaul link between the macro-cell and the relay node has a major impact on the performance of the multi-hop transmission. This paper presents a measurement-based study focusing on the performance evaluation of the relay backhaul link for different potential relay locations and antenna configurations in a real urban macro-cell scenario. Based on the assumption that a similar network deployment would apply for LTE-A, a fully operational 3G network has been used for measuring both received signal strength and Signal-to-Interference-Ratio (SIR). Furthermore, the results have been used to estimate the performance of the multi-hop transmission under simplifying assumptions. The experimental results show that by increasing the relay height from 2.4 m to 5 m, the received signal strength improves on average by 1.7 dB for omnidirectional antennas. When a directional antenna is mounted at 5 m and pointed towards the serving macro cell, significant SIR gains (around 5.9 dB) and throughput improvements are achieved at the locations where the relay node and the macro-cell are in Line-of-Sight (LOS).

Base station antenna downtilt is one of the most important parameters for optimizing a cellular network with tight frequency reuse. By downtilting, inter-site interference is reduced, which leads to an improved performance of the network. In this study we show that a simple geometrical-based extension to standard empirical path loss prediction models can give quite reasonable accuracy in predicting the signal strength from tilted base station antennas in small urban macro-cells. Our evaluation is based on measurements on several sectors in a 2.6 GHz Long Term Evolution (LTE) cellular network, with electrical antenna downtilt in the range from 0 to 10 degrees, as well as predictions based on ray-tracing and 3D building databases covering the measurement area. Although the calibrated ray-tracing predictions are highly accurate compared with the measured data, the combined LOS/NLOS COST-WI model with downtilt correction performs similarly for distances above a few hundred meters. Generally, predicting the effect of base station antenna tilt close to the base station is difficult due to multiple vertical sidelobes.

The deployment of new network equipment is resulting in increasing energy consumption in mobile broadband networks (MBNs). This contributes to higher CO2 emissions. Over the last 10 years MBNs have grown considerably, and are still growing to meet the evolution in traffic volume carried in wireless networks. To save energy in MBNs, one of the options is to turn off parts of the network equipment in areas where traffic falls below a specific predefined threshold. This paper looks at a methodology for identifying periods of the day when cells or sites carrying low traffic are candidates for being totally or partly switched off, given that the decrease in service quality can be controlled gracefully when the sites are switched off. Based on traffic data from an operational network, potential average energy savings of approximately 30% with some few low traffic cells/sites reaching up to 99% energy savings can be identified.

Due to the poor outdoor-to-indoor propagation into buildings, dedicated wireless systems installed inside the buildings is often preferred for providing indoor users with high-data-rate services. We study the typical in-building wireless solutions - distributed antenna system and small cell Femto system - together with another multi-cell system using our proposed centralized scheduling scheme. In our previous work, their performance is evaluated and compared in the LTE downlink context with full buffer traffic. Compared to real mobile networks, the full buffer traffic model is usually a worst-case estimation of traffic load which causes severe interference conditions. Especially for Femto cells with universal frequency reuse it degrades system performance and may lead to biased conclusions on the relative performance of the different in-building solutions. In this study, we use a more realistic traffic model with fixed buffer size and Poisson arrival. Our new results show better performance for Femto cells with frequency reuse 1 at light to medium load, although the intelligent distributed system still obtains considerable better cell edge user throughput for the same number of access points.

Small cells are popular deployment options for coverage holes and capacity hotspot areas. Due to the poor outdoor-to-indoor propagation property of in-building environment, a dedicated wireless system installed inside the building is often preferred for providing indoor users high-data-rate services. Distributed antenna systems and Femto cells are cost-efficient techniques for this application. In this paper, their performance is evaluated in an LTE downlink context along with a proposed joint scheduling system, which maximizes the supported number of users under a QoS constraint. The selection of the enterprise building model includes a general office building model described in the WINNER II project and a site-specific office building with large scale path-loss values retrieved from measurements. Results show superior performance of the Femto system compared to DAS in providing high-data-rate services in most cases with a quality-guaranteed scheduler, while the centralized joint scheduling system gives the best performance. The centralized scheme can also help improve the system robustness in obtaining high performance even in the situation where access points are placed non-optimally.

In the Long Term Evolution system Discontinuous Transmission and Reception (DRX/DTX) has been introduced to extend the terminal battery lifetime. In this paper, we study the energy-saving provided by this mechanism and the impact on the QoS performance of Voice over IP (VoIP) traffic under dynamic and semi persistent packet scheduling strategies. Simulations and analytical results show that the DRX/DTX scheme can reduce the terminal power consumption without compromising the required VoIP QoS in terms of maximum air-interface delay. However, it does not provide any further power savings if the terminal is asleep for a period longer than 20 ms. It is shown that the power savings are larger for semi persistent scheduling than for dynamic packet scheduling at the cost of a lower spectral efficiency.

This paper focuses on reducing the uplink overhead caused by Acknowledgement (ACK)/Non-acknowledgement (NACK) signaling in an Long Term Evolution (LTE)-Advanced system. Such a system typically aggregates multiple Component Carrier (CC)s to obtain a wide bandwidth. Usually it has much larger feedback overhead than the single-CC system, and hence reducing the overhead is of special importance. A technique called ACK/NACK bundling has been used for the overhead reduction of the ACK/NACK signaling. Along with the overhead reduction, the downlink performance is also degraded. The tradeoff between the downlink performance and the overhead is analyzed under various load conditions and antenna configurations. The presented results can be used for selecting the proper bundling scheme based on specific system setting.

Long Term Evolution (LTE)-Advanced is expected to aggregate multiple Component Carrier (CC)s to fulfil the high data rate requirement. It may serve users with different capabilities in accessing these CCs, e.g., some can access all CCs, whereas some may operate on only one CC. This gives challenges to the packet scheduler to maximize the system performance over all CCs. In this paper we provide a mathematical model of the log-measure utility in an LTE-Advanced system, and give proof that our previously developed cross-CC Proportional Fair (PF) packet scheduler maximizes this utility. System level simulations are performed, which confirm that cross-CC PF scheduling offers much higher utility than independent PF and channel blind schedulers. This scheduler is then generalized to adjust the resource sharing among users. It can trade off between average cell throughput and cell edge user throughput. However, any adjustment in the resource sharing leads to a loss in utility.

The ambitious data rate target of the Long Term Evolution - Advanced (LTE-A) systems, which are currently being standardized by the 3rd Generation Partnership Project (3GPP), can only be achieved by using advanced Multiple Input Multiple Output (MIMO) antenna techniques on both uplink and downlink. In this paper, the focus is on LTE-A uplink and we discuss the suitability of two options for the closed loop precoded MIMO transmission. The first option is to use the same codebook of precoding matrices defined for LTE downlink, while the second option exploits the Singular Value Decomposition (SVD) of the channel matrix, which could theoretically achieve the MIMO capacity. Qualitative benefits of both solutions are discussed. Link level simulation results show that, the SVD-based approach only lead to a poor performance gain in terms of spectral efficiency over the LTE downlink codebook because of the losses due to the quantization of the right singular vectors of the channel matrix. Since SVD-based solution doesn't even exploit some useful properties (e.g., power balance over the antennas) which LTE Release 8 codebook offers, the latter results to be a better candidate for the closed loop MIMO transmission in LTE-A uplink.

A multiple component carrier (CC) solution has been agreed as the underlying structure of the Long Term Evolution - Advanced (LTE-A) systems, which are currently being standardized by the 3rd Generation Partnership Project (3GPP). In this deployment, the bundling of Modulation and Coding Scheme (MCS) and Hybrid Automatic Repeat Request (HARQ) parameters across multiple CCs is foreseen to maintain the feedback signaling comparable with the one of the previous LTE Release 8. This paper focuses on the transmission over multiple CCs in LTE-A Uplink. Issues related to the bundling of the link level parameters is discussed and a simple Codeword (CW) mixing strategy is proposed to boost the spectral efficiency performance while keeping low feedback overhead. Results show that, combined HARQ/MCS bundling can achieve the same performance of HARQ only bundling when used together with our proposed CW mixing strategy, with the advantage of a lower feedback overhead. CW mixing also leads to similar spectral efficiency when the bundling is performed over 2 and 3 CCs. The use of a turbo Successive Interference Cancellation (turbo SIC) receiver further improves the spectral efficiency, especially when antenna gain imbalance (AGI) occurs.

This paper studies the different ways of extending wireless coverage for high data rates and improving the data capacity in a building. The solutions considered include deployments of single or multiple small base stations, i.e. Picocell or Femtocell, and distributed antenna system, operated on the same frequency as the macro cellular network. We look at the radio performance of each solution in a LTE downlink context with in-building path loss values retrieved from real-life measurements. The performance is compared by means of maximum supportable user numbers and average system throughput. Potential gains by hard frequency reuse in the building and QoS based packet scheduling are examined. Simulation results show the robustness of the proposed distributed antenna system and the conditions for multi-Femtocell deployment.

in this paper we address the problem of reducing the feedback for the downlink transmission in multi-carrier systems. In these systems multiple Component Carriers (CCs) are aggregated together to form a wide spectrum. Consequently, a large feedback overhead is required to report the channel quality information over such a wide bandwidth. We first generalize two existing feedback reduction techniques, and then propose a new one. These techniques use different feedback schemes across the CCs, or allow some CCs to be un-reported, for the purpose of reducing the amount of feedback. Performance for the investigated techniques is evaluated in a realistic system setting with different traffic conditions and terminal categories. Based on the obtained results, the selection of proper feedback reduction technique under different load conditions can be made. The findings are useful for reducing the feedback overhead in future generation wireless communication systems that operate over multiple CCs.

Abstract-In this paper we focus on resource allocation for next generation wireless communication systems with aggregation of multiple Component Carriers (CCs), i.e., how to assign the CCs to each user, and how to multiplex multiple users in each CC. We first investigate two carrier load balancing methods for allocating the CCs to the users- Round Robin (RR) and Mobile Hashing (MH) balancing by means of a simple theoretical formulation, as well as system level simulations. At Layer-2 we propose a simple cross-CC packet scheduling algorithm that improves the coverage performance and the resource allocation fairness among users, as compared to independent scheduling per CC. The Long Term Evolution (LTE)-Advanced is selected for the case study of a multi-carrier system. In such a system, RR provides better performance than MH balancing, and the proposed simple scheduling algorithm is shown to be effective in providing up to 90% coverage gain with no loss of the overall cell throughput, as compared to independent scheduling per CC.

In this paper, we present a novel iterative receiver for MIMO-OFDM systems with synchronous interferers. The receiver is derived based on the Kullback-Leibler divergence minimization framework, and combines channel estimation, interference cancellation and residual noise estimation in an iterative manner. By using both the pilot and data symbols, the channel estimator improves the accuracy of the estimates in each iteration, which leads to a more effective interference cancellation and data detection process. A performance evaluation based on Monte-Carlo simulations shows that the proposed scheme can effectively mitigate the effect of interferers, and operates very close to the single-user performance even in severe interference scenarios.

In this paper, we present a novel approach for pilot-aided channel estimation in OFDM systems with synchronous co-channel interference. The estimator is derived based on the Kullback-Leibler divergence minimization framework. The obtained solution iteratively updates both the desired user's and the interferer's channels, using a combination of linear minimum mean squared-error (LMMSE) filtering and interference cancellation, avoiding the complex matrix inversions involved in the full LMMSE channel estimation approach. Estimation of the noise variance is also included in the iterative algorithm, accounting for Gaussian noise and residual interference after each iteration. The estimates of both channels are used at the equalizer to reject the interfering signal, thus mitigating the degradation due to co-channel interference. Simulation results show that the receiver using the proposed estimator performs as good as the one employing the full LMMSE estimator and very closely to a receiver having perfect knowledge of the channel coefficients.

In this paper we focus on LTE-Advanced with backward compatibility, which serves a mixture of LTE-Advanced and LTE-Rel'8 users. Aggregation of multiple component carriers (CCs) to form a wide spectrum is assumed in order to fulfill the bandwidth requirement for the next generation systems, thereby leading to a multi-carrier system. Although a LTE-Advanced user can simultaneously access all the CCs, a LTE-Rel'8 user is restricted to operate on a single CC at a time. Different methods for balancing the load across these CCs will affect the system performance. This is investigated through both analytical methods and system level simulations. Bearing in mind that the LTE-Advanced users are scheduled on more CCs than the LTE-Rel'8 users, we propose a simple cross CC packet scheduling algorithm that improves the resource allocation fairness among the two categories of users. This simple scheduling algorithm is shown to be effective in providing better coverage performance with no loss of the overall cell throughput, as compared to independent scheduling per CC.

In this paper we focus on LTE-Advanced performance under bursty traffic conditions, and devote our effort to the different methods for balancing the load across multiple carriers. These carriers are the component carriers (CCs) that belong to the same carrier frequency. They are bonded together in order to fulfill the requirement of wide spectrum in LTE-Advanced. We first derive the analytical model for a bursty birth-death traffic model with fixed payload size for OFDMA with different frequency domain packet schedulers. Applying this model for a multi-carrier system, we compute the performance for different system setups. The obtained analytical results are verified using extensive system level simulations. Based on the analytical and simulation results, it is suggested to assign the users on all CCs if a cell is not heavily loaded. Otherwise, assign each user with only one CC using the load balancing method of Round Robin is preferable, in the sense that it maintains good performance with low uplink overhead.

In a multi-component carrier LTE-Advanced system, a user can simultaneously be scheduled on all component carriers (CCs). For the base station to perform radio channel aware packet scheduling, each user ideally has to feedback information corresponding to all CCs. This results in a potentially high amount of uplink overhead. Furthermore, a user in a power limited situation may experience outage because of insufficient power for the required feedback. In this paper we first propose several techniques at different layers for the overhead reduction, as well as protecting the users from being in the outage situation. Afterwards, we show how these techniques can be integrated in a LTE-Advanced system. A weighted proportional fair scheduler is also proposed to maintain good performance with a reduced amount of overhead. Extensive simulation results are presented in the end for analyzing the proper trade-off between performance and overhead reduction and outage protection.

The paper deals with turbo detection techniques for Single User Multiple-Input-Multiple-Output (SU MIMO) antenna schemes. The context is on the uplink of the upcoming Long Term Evolution - Advanced (LTE-A) systems. Iterative approaches based on Parallel Interference Cancellation (PIC) and Successive Interference Cancellation (SIC) are investigated, and a low-complexity solution allowing to combine interstream interference cancellation and noise enhancement reduction is proposed. Performance is evaluated for Orthogonal Frequency Division Multiplexing (OFDM) and Single Carrier Frequency Division Multiplexing (SC-FDM) as candidate uplink modulation schemes for LTE-A. Simulation results show that, in a 2times2 antenna configuration, the turbo processing allows a consistent improvement of the link performance, being SC-FDM the one having higher relative gain with respect to linear detection. The turbo receiver's impact is however much reduced for both modulation schemes in a 2times4 configuration, due to the higher diversity gain provided by the additional receive antennas.

The 3rd generation partnership project (3GPP) defined the requirements for the upcoming long term evolution advanced (LTE-A) systems, aiming at peak spectral efficiencies of 30 bit/s/Hz in the downlink and 15 bits/s/Hz in the uplink. These ambitious targets can be accomplished only by using advanced multiple input multiple output (MIMO) antenna techniques. In this paper, we evaluate closed loop precoded multirank transmission for single carrier frequency division multiplexing (SC-FDM) as selected uplink modulation scheme by using the precoding codebook defined for LTE downlink. Its performance is compared with orthogonal frequency division multiplexing (OFDM). Results show that OFDM outperforms SC-FDM for medium-high ranks, but the gap can be reduced by adding further diversity branches. While narrowband precoding shows considerable gain over open loop transmission for all ranks, wideband precoding works with a very small feedback overhead but results to be a valid option mainly for low-rank transmission, where the low peak-to-average power ratio (PAPR) of SC-FDM signals is also preserved.

In Frequency Division Duplex (FDD) systems or Time Division Duplex (TDD) systems with perfect Uplink (UL)/Downlink (DL) alignment, all UL transmissions receive interference only from other UL links and vice versa. However, take into consideration one of the most important benefits that TDD offers, i.e., dynamic UL/DL switching points, the UL and DL transmission can be misaligned. This means UL might be corrupted by DL, and vice versa. The loss of network time-synchronization among different cells makes things even more complicated for TDD systems. Many techniques are developed to achieve network synchronization, e.g., GPS based or IEEE 1588 based techniques. In this paper, the effect that different synchronization and UL/DL switching points introduce to the system performance is studied. The purpose is to find out the benefit that synchronization can offer. Based on the observations, it is suggested to achieve at least loose network synchronization.

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.

Turbo equalization is known as an advanced iterative equalization and decoding technique that allows to enhance the performance of the data transmission over a frequency selective fading channel. The turbo equalizer will result in extra receiver complexity, but isolated to the base-station, which does not have stringent power constraints. In this paper, a turbo equalization technique to improve Single Carrier Frequency Division Multiple Access (SC-FDMA) performance is proposed. A new adaptive coefficients solution for frequency domain equalization is considered. The work is in the context of UTRA Long Term Evolution (LTE) Uplink. The performance is evaluated for 1x2 Single Input Multiple Output (SIMO) antenna configuration in a 6 paths Typical Urban (TU-06) channel profile. For assessment purpose, the results are compared with SC-FDMA MMSE and OFDMA schemes. Simulation results show that the turbo equalizer can improve the BLER performance around 1 dB with only a few iterations, and improve the SC-FDMA performance over OFDM, especially at high coding rate.

In this paper, we investigate different multiple-input multiple-output (MIMO) receiver structures based on MMSE filtering and sequential interference cancellation (SIC) for the downlink of the 3GPP long term evolution (LTE) system. We divide them into two approaches: symbol-SIC receivers, in which the detection and interference cancellation is done independently for each subcarrier, and codeword-SIC structures, in which the processing is carried out for each independently-coded stream by including the turbo-decoder inside the feedback loop. The results show that symbol-SIC receivers need to take into account the propagation of errors in the interference cancellation to provide the turbo decoder with reliable soft bit values. However, these are clearly outperformed by codeword-SIC schemes, due to the error correction capabilities of the turbo-decoder inside the feedback loop. We show that the best tradeoff between computational complexity and receiver performance is achieved by only cancelling the interference of a codeword when this has been successfully decoded.

In this paper we investigate the impact of in-band interference on the uplink multiple access of UMTS Terrestrial Radio Access, long term evolution (UTRA LTE). In- band and out-of-band interference arise as a result of transmitter imperfections. Out-of- band, or adjacent channel, interference can be controlled by a spectral shaping filter. However, the shaping filter cannot control the leakage within the system bandwidth, and the resulting leakage can interfere with other users' transmission in the uplink multiple access. The situation is emphasized when the resource block allocation size is small, and when the interfering signal is received at higher power spectral density (PSD). The effect of frequency offset and different PSD level from the UE interferers to a victim UE is studied. The impact on different UE resource block size allocation is also investigated. The results are obtained from an LTE uplink link level simulation. It is shown that a significant SNR degradation is observed at the victim UE with smaller resource block size, when evaluated in a realistic channel. Considering that the frequency offset can be maintained below 200 Hz and PSD level offset below 10 dB, the SNR loss at 10% BLER target is less than 1 dB.

In a pre-coded Multi User Multiple Input Multiple Output (MU-MIMO) system, the channelization can be done either by using any of the two basic access techniques, namely Orthogonal Frequency Division Multiple Access (OFDMA) and Space Division Multiple Access (SDMA), or by combining them. From resource allocation point of view, choice of any technique will require different fairness conditions among users. In this paper, we have studied these different fairness conditions when combined with basic or joint access schemes mentioned above, while applied in a MU-MIMO based UTRA-LTE system. We have evaluated the resource allocation fairness issue when two well-known linear MU-MIMO precoding is used on a UTRA-LTE system. User grouping issue is dealt with when SDMA component is considered in the system. The results in this work provides an indicative analysis of the usability of different channelization techniques for considered system.

In this paper, an iterative enhancement of the robust Wiener filter (RWF) estimator is presented for a turbo-coded orthogonal frequency division multiplexing (OFDM) system under the umbrella of the 3GPP long term evolution. The proposed scheme can operate with uncoded or coded feedback, and outperforms the conventional linear RWF in the whole signal-to-noise ratio (SNR) range with both approaches. Results show that most of the gain is obtained in the first iteration of the algorithm, and better performance is achieved with the coded feedback scheme. A good tradeoff between accuracy and complexity is achieved by selecting a low number of turbo coding iterations (TCI) in the iterative loop and concentrating most of them at the final decoding stage. Following this design, cell spectral efficiency gains of around 2.7% and 6.5% can be obtained with respect to linear RWF for micro- and macro-cell scenarios respectively.

In future time division duplex (TDD)-based broadband wireless systems, it will be possible to exploit the channel reciprocity to implement channel state information (CSI)-based multi user multiple input multiple output (MU-MIMO) techniques, which will ensure highly efficient spectrum usage. To increase the cell coverage while ensuring the quality of service (QoS) for all UEs across the cell area, fairness should be maximized as much as possible. This paper presents a novel way to help improving fairness performance in the physical layer, via fair power allocation together with resource allocation, in MU-MIMO precoding scenarios where the common approach of guaranteeing fairness at MAC layer is not feasible. The results presented in this paper show that the proposed algorithm is able to reduce the system outage event to a large extent, thus increases fairness.

This paper addresses the performance of spatial division multiplexing (SDM) multiple-input multiple-output (MIMO) techniques together with frequency domain packet scheduling (FDPS) in both theory and practice. We start with a theoretical analysis under some ideal assumptions to derive the performance bounds of SDM-FDPS. To facilitate the analysis, a unified SINR concept is utilized to make a fair comparison of MIMO schemes with different number of spatial streams. The effect of packet scheduling is included in the post-scheduling SINR distribution using an analytical model. Based on that, the performance bounds are obtained with a more realistic SINR to throughput mapping metric. The system-level performance of SDM-FDPS has been evaluated under practical constraints using detailed simulations based on the UTRAN long term evolution (LTE) downlink cellular system framework. The purpose is to investigate the impact of realistic factors on performance. Results confirm that the combination of SDM and FDPS can increase the spectral efficiency significantly, particularly in a micro-cell scenario, and up to 30%-60% gain is observed over 1times2 with FDPS depending on the traffic models considered. Finally, the more practical simulation results are compared against the theoretical performance bounds. A performance loss is seen in the simulations due to realistic coding/modulation, impact of frequency selectivity, signalling constraints, imperfect channel quality indicator (CQI), etc.

This paper studies common linear frequency direction pilot- symbol aided channel estimation algorithms for orthogonal frequency division multiplexing in a UTRA long term evolution context. Three deterministic algorithms are analyzed: the maximum likelihood (ML) approach, the noise reduction algorithm (NRA) and the robust Wiener (RW) filter. A closed form mean squared error is provided for these three algorithms. Analytical and simulation results show that, in the presence of virtual subcarriers, the ML can suffer large performance degradation due to ill-conditioned matrix issues. A solution to this problem is to use the Tikhonov regularization method giving the NRA. The equivalence between the NRA and the RW is proved analytically. A practical implementation of the NRA and RW is proposed based on partial-input partial-output FFT, leading to 6 to 8 times lower complexity than the reference implementation.

In this paper we present an initial performance evaluation of the 3GPP UTRA long term evolution (UTRA LTE) uplink with baseline settings. The performance results are obtained from a detailed UTRA LTE uplink link level simulator supporting OFDMA and SC-FDMA schemes. The basic transmission scheme for uplink direction is based on single-carrier transmission in the form of DFT spread OFDM with an MMSE receiver. Two antenna configurations, SISO and 1times2 SIMO are considered in the analysis of spectral efficiency in addition to adaptive modulation and coding (AMC) and L1-HARQ. For assessment purposes, the performance results of SC-FDMA are compared with OFDMA. It is shown that 1times2 SIMO greatly increases the spectral efficiency of SC-FDMA making it comparable to OFDMA, especially for high coding rate. Furthermore, SC-FDMA has a flexibility to increase BLER performance by exploiting frequency diversity.

In this paper we investigate the effect of modelled RF transmitter impairments on UTRA Long Term Evolution (LTE) uplink link performance. Nonlinear power amplifier, gain imbalance, phase imbalance, and phase noise are considered. The main contributions of this work is assessment of the relation between Error Vector Magnitude (EVM) and link performance loss due to each impairment and the investigation of a white Gaussian noise source in the transmitter as an equivalent model of the impairment. The results obtained are based on the UTRA LTE uplink parameter settings. Results show that the EVM is a good measure to estimate the link level performance loss for numerous impairments. The performance degradation in AWGN and a frequency selective fading when using a white noise source as an equivalent transmitter RF impairment model, fits well with the other impairments in the anticipated range of EVM. An analytical formulation describing the effect of the white noise source in the SNR loss fits similarly with the simulation results. With 16 QAM rate 3/4, an EVM value of 8% corresponds to an SNR loss of approximately 0.5 dB.

This paper addresses the performance of spatial division multiplexing (SDM) multiple-input multiple-output (MIMO) techniques together with frequency domain packet scheduling (FDPS) based on UTRAN long term evolution (LTE) downlink. Two SDM concepts currently considered in 3GPP are the single-user (SU-) and the multi-user (MU-) MIMO. For MU-MIMO, multiple users can be scheduled on different streams on the same time-frequency resource, while SU-MIMO restricts one time-frequency resource to a single user. Both concepts are analyzed against the 1times2 maximal ratio combining (MRC) case, using the proportional fair (PF) criterion extended to frequency and spatial domains. The realistic finite buffer best effort traffic model is used in the study. Results show that in the macrocell scenario, the combination of FDPS and SDM (SDM-FDPS) without preceding achieves only marginal gain in cell throughput, due to limited SINR dynamic range. The gain is increased to around 20% when precoding is applied. In the micro-cell scenario, the gain of SDM-FDPS over the reference scheme is increased up to 35% with precoding.

MIMO techniques in the spatial division multiplexing (SDM) mode have demonstrated tremendous performance potential when a single user link is considered. Recent studies have shown that frequency domain packet scheduling (FDPS) can provide a significant gain when combined with SDM (SDM-FDPS) by exploiting the multi-user diversity gain over frequency as well as the spatial domains. However, the increased signaling requirements in both uplink and downlink may prevent its practical use. In this paper several effective approaches are identified for reducing the signaling requirements for SDM-FDPS while still maintaining acceptable performance. Results show that the performance loss can be kept within 10% for a uplink signaling reduction of 88% and a downlink signaling reduction of 30%.

In this paper, the effects of phase noise on the spectral efficiency of the next generation of OFDM based mobile systems with channel estimation is investigated. The simulation context and parameter settings are taken from the 3GPP Evolved UTRA (E-UTRA) study item, focusing on an OFDM downlink single antenna system in 20 MHz bandwidth. Phase noise is modeled as a Wiener-Levy process and several phase noise powers are evaluated. The OFDM coherent detection method is based on pilot assisted channel estimation (PACE) with Wiener based frequency domain interpolation and second order Gaussian interpolation for the time domain interpolation. The cell level spectral efficiency is also evaluated for micro and macro-cell scenarios. The simulation results indicate that the phase noise effect in E-UTRA downlink can be reduced by using high performance local oscillator or by placing pilots in every OFDM symbols

Performance evaluation of closed-loop transmit diversity (CETD) for 3GPP UTRA long term evolution (ETE) is addressed in this paper. To reduce the feedback and keep comparable performance with optimum weighting, we reduce the feedback by means of quantization and subcarrier grouping. Theoretical analysis on loss of different quantization resolution and size of groups shows the tradeoffs between signalling overhead and performance. Although CETD can bring array and diversity gain, the interaction of CETD with some of the essential features of UTRA ETE system like adaptive modulation coding (AMC)-based time domain link adaptation and hybrid ARQ may affect the attainable spectral efficiency gain from CETD. In this paper, detailed link level simulation is carried out to investigate this interaction with two transmit antennas assuming one or two receive antennas. Simulation results show that the cell level gain is quite limited for CETD, in which only 9.8% and 18% gain is observed in micro- and macro- cell respectively with two receive antennas and a grouping size of 25

This paper evaluates spectral efficiency performance of the 3GPP Evolved UTRA (E-UTRA) downlink with baseline settings. A detailed link level tool has been developed including the majority of 3GPP E-UTRA link chain processing modules such as time-domain link adaptation and LI HARQ. Since MIMO is an integral part of the new system, we include four basic multiple antenna configurations in the analysis, namely the SISO, 1x2 SIMO, 2x2 SFC and 2x2 BLAST schemes. Since the BLAST is very sensitive to channel estimation error in cell edge, a case denoted as adapMIMO is considered as well, where the SFC is taken as a backup for the BLAST in cell edge. The system bandwidth is fixed at 20 MHz and a Typical Urban channel model is assumed for both macrocell and microcell evaluations. Simulation results show that in macrocell scenario, the spectral efficiency performance gain of SIMO over SISO is up to 54%, while SFC shows an additional gain of 14% over SIMO. Although the adapMIMO scheme has similar performance as SFC in the macrocellular case, it produces about 30% spectral efficiency gain in the microcell scenario.

This paper addresses the potential gain of including MIMO adaptation into Link adaptation (LA) Layer. Theoretical analysis is carried out from a new perspective, namely the distribution of unified instantaneous signal to interference and noise ratio (unified SINR) which encompasses MIMO schemes with different number of effective spatial streams and/or different receiver structures. Based on that, the capacity of LA including MIMO adaptation is formulated. Besides the theoretical analysis, issues concerning the practical application of LA including MIMO adaptation are discussed. A two dimensional lookup table (LUT) based on average SINR and SINR ratio is investigated for the selection of MIMO, modulation and coding set every transmission time interval. Results from simulations with real time domain LA show that significant spectral efficiency gain can be achieved as compared to the case of LA without MIMO adaptation.

This paper presents an autocorrelation model of the slow fading process in a small urban macro cell. The model is obtained by a combination of parametric system identification and classical spectral estimation procedures, and is based on measured data. An analytic expression for the autocorrelation function of the resulting ARMA (2,1)-autoregressive moving average-model is given and compared to other results. The model predicts about the same overall decorrelation distance, but a faster correlation roll-off for small lags.