The rapid evolution of wireless technologies has intensified interest in open and fully programmable radio access networks for whole-stack research, innovation, and evaluation of emerging solutions. Large-scale wireless living labs, such as ARA, equipped with real-world infrastructure play a vital role in this evolution by enabling researchers to prototype and evaluate advanced algorithms for next-generation wireless systems in outdoor and over-the-air environments benefiting from real-world fidelity and end-to-end programmability. However, at the core of this innovation is the performance in terms of coverage and reliability of these wireless living labs. For instance, interfacing power amplifiers and low noise amplifiers with software-defined radios (SDRs) for experimenting outdoors introduces issues in random access procedure—a process crucial in establishing connectivity between user equipment (UE) and the core network in 5G and 6G systems. Therefore, to ensure seamless connectivity and reliable communications in open-source 5G software stacks such as OpenAirInterface (OAI), we propose a slot-based approach to the 5G random access procedure leveraging full downlink (DL) and uplink (UL) slots instead of using special or mixed slots. We highlight how this approach achieves reliable 5G connectivity over 1 mile—the longest communication range that has been achieved so far in real-world settings using open-source 5G software stacks and the Universal Software Radio Peripheral (USRP) SDRs. We also demonstrate that, in a highly obstructed environment such as an industrial setting, we can increase the probability of a successful random access procedure to 90%–100% when we use at least 9 OFDM symbols to transmit msg2 and msg3.

The development of 6G wireless technologies is rapidly advancing, with the 3rd Generation Partnership Project (3GPP) entering the pre-standardization phase and aiming to deliver the first specifications by 2028. This paper explores the OpenAirInterface (OAI) project, an open-source initiative that plays a crucial role in the evolution of 5G and future 6G networks. OAI provides a comprehensive implementation of 3GPP and O-RAN compliant networks, including Radio Access Network (RAN), Core Network (CN), and software-defined User Equipment (UE) components. This paper details the history and evolution of OAI, its licensing model, and the various projects under its umbrella, such as RAN, the CN, and the Operations, Administration and Maintenance (OAM) projects. It also highlights the development methodology, Continuous Integration/Continuous Delivery (CI/CD) processes, and end-to-end systems powered by OAI. Furthermore, the paper discusses the potential of OAI for 6G research, focusing on spectrum, reflective intelligent surfaces, and Artificial Intelligence (AI)/Machine Learning (ML) integration. The open-source approach of OAI is emphasized as essential for tackling the challenges of 6G, fostering community collaboration, and driving innovation in next-generation wireless technologies.

Open Radio Access Networks (RANs) leverage disaggregated and programmable RAN functions and open interfaces to enable closed-loop, data-driven radio resource management. This is performed through custom intelligent applications on the RAN Intelligent Controllers (RICs), optimizing RAN policy scheduling, network slicing, user session management, and medium access control, among others. In this context, we have proposed dApps as a key extension of the O-RAN architecture into the real-time and user-plane domains. Deployed directly on RAN nodes, dApps access data otherwise unavailable to RICs due to privacy or timing constraints, enabling the execution of control actions within shorter time intervals. In this paper, we propose for the first time a reference architecture for dApps, defining their life cycle from deployment by the Service Management and Orchestration (SMO) to real-time control loop interactions with the RAN nodes where they are hosted. We introduce a new dApp interface, E3, along with an Application Protocol (AP) that supports structured message exchanges and extensible communication for various service models. By bridging E3 with the existing O-RAN E2 interface, we enable dApps, xApps, and rApps to coexist and coordinate. These applications can then collaborate on complex use cases and employ hierarchical control to resolve shared resource conflicts. Finally, we present and open-source a dApp framework based on OpenAirInterface (OAI). We benchmark its performance in two real-time control use cases, i.e., spectrum sharing and positioning in a 5th generation (5G) Next Generation Node Base (gNB) scenario. Our experimental results show that standardized real-time control loops via dApps are feasible, achieving average control latency below 450 microseconds and allowing optimal use of shared spectral resources.

As Fifth generation (5G) cellular systems transition to softwarized, programmable, and intelligent networks, it becomes fundamental to enable public and private 5G deployments that are (i) primarily based on software components while (ii) maintaining or exceeding the performance of traditional monolithic systems and (iii) enabling programmability through bespoke configurations and optimized deployments. This requires hardware acceleration to scale the Physical (PHY) layer performance, programmable elements in the Radio Access Network (RAN) and intelligent controllers at the edge, careful planning of the Radio Frequency (RF) environment, as well as end-to-end integration and testing. In this paper, we describe how we developed the programmable X5G testbed, addressing these challenges through the deployment of the first 8-node network based on the integration of NVIDIA Aerial RAN CoLab Over-the-Air (ARC-OTA), OpenAirInterface (OAI), and a near-real-time RAN Intelligent Controller (RIC). The Aerial Software Development Kit (SDK) provides the PHY layer, accelerated on Graphics Processing Unit (GPU), with the higher layers from the OAI open-source project interfaced with the PHY through the Small Cell Forum (SCF) Functional Application Platform Interface (FAPI). An E2 agent provides connectivity to the O-RAN Software Community (OSC) nearreal-time RIC. We discuss software integration, network infrastructure, and a digital twin framework for RF planning. We then profile the performance with up to 4 Commercial Off-the-Shelf (COTS) smartphones for each base station with iPerf and video streaming applications, as well as up to 25 emulated User Equipments (UEs), measuring a cell rate higher than 1.65 Gbps in downlink and 143 Mbps in uplink.

The fifth generation new radio (5G NR) technology is expected to fulfill reliable and accurate positioning requirements of industry use cases, such as autonomous robots, connected vehicles, and future factories. Starting from Third Generation Partnership Project (3GPP) Release-16, several enhanced positioning solutions are featured in the 5G standards, including the multi-cell round trip time (multi-RTT) method. This work presents a novel framework to estimate the round-trip time (RTT) between a user equipment (UE) and a base station (gNB) in 5G NR. Unlike the existing scheme in the standards, RTT can be estimated without the need to send timing measurements from both the gNB and UE to a central node. The proposed method relies on obtaining multiple coherent uplink wide-band channel measurements at the gNB by circumventing the timing advance control loops and the clock drift. The performance is evaluated through experiments leveraging a real world 5G testbed based on OpenAirInterface (OAI). Under a moderate system bandwidth of 40MHz, the experimental results show meter level range accuracy even in low signal-to-noise ratio (SNR) conditions.

Due to an ever-expansive network deployment, numerous questions are being raised regarding the energy consumption of the mobile network. Recently, Non-Terrestrial Networks (NTNs) have proven to be a useful, and complementary solution to Terrestrial Networks (TN) to provide ubiquitous coverage. In this paper, we consider an integrated TN-NTN, and study how to maximize its resource usage in a dynamic traffic scenario. We introduce BLASTER, a framework designed to control User Equipment (UE) association, Base Station (BS) transmit power and activation, and bandwidth allocation between the terrestrial and non-terrestrial tiers. Our proposal is able to adapt to fluctuating daily traffic, focusing on reducing power consumption throughout the network during low traffic and distributing the load otherwise. Simulation results show an average daily decrease of total power consumption by $45 \%$ compared to a network model following 3GPP recommendation, as well as an average throughput increase of roughly $250 \%$. Our paper underlines the central and dynamic role that the NTN plays in improving key areas of concern for network flexibility.

The third generation partnership project (3GPP) has defined ultra-reliable low latency communication (URLLC) as one of the key 5G competencies to provide high network reliability and low latency. The configured grant (CG) transmission, defined in 3GPP Release-15, is a technique that automatically transmits a URLLC packet with a configured number of repetitions to increase reliability. In this paper, we propose enhanced modeling for CG transmission considering the communication channel state to evaluate the network performance. The results show how to configure CG transmission to reach a defined probability of success for decoding the packets.

Positioning a user terminal based on cellular signals is an attractive solution in situations where accurate positioning based on global navigation satellite systems (GNSS) is not possible, such as inside buildings. The 5G New Radio (NR) networks based on 3GPP have introduced several enhanced features to allow the accurate positioning of user terminals. Especially Frequency Range 2 (FR2) mmWave setups are attractive for localization because the large bandwidths allow for high-resolution estimation of the Time Difference of Arrival (TDoA) while the beamforming capabilities can be exploited to estimate the Angle of Arrival (AoA) or Angle of Departure (AoD) of the signals.In this work, we propose a new UE-based positioning algorithm that combines the Downlink Time Difference of Arrival (DL-TDoA) and Downlink Angle of Departure (DL-AoD) information estimated from the downlink positioning reference signals (DL-PRS) introduced in 3GPP Rel-16. TDoA is a widely used horizontal positioning technique that does not require tight synchronization between base stations and mobile stations. Moreover, multiple antennas beamforming on base stations leads to high vertical positioning accuracy with AoD. We use ray-tracing-based site-specific channel models to evaluate our joint positioning algorithm’s performance in an Indoor Factory (InF) scenario. The simulation results show sub-meter user localization error which is a significant improvement compared to applying the previous methods separately.

5G, the latest generation of cellular technology, targets not only enhanced data rates but also new applications which require, e.g., ultra-reliable low latency communication. Verticals like industrial automation or automotive, which want to make use of this type of wireless services, need experimental deployments to test the performance of 5G in various modes and environments for their use cases. Due to the ongoing stan-dardization process, experimental 5G networks based on open-source frameworks are especially well suited, as they provide the possibility to easily implement new features introduced by the yearly 5G standard releases. We thus present an experimental 5G standalone deployment, based on the OpenAirInterface, which is an open-source framework, that is being used both, commercially and for academic purposes. We evaluate coverage parameters including reference signal received power, reference signal received quality, and signal to interference and noise ratio both for single user and multiple user scenarios. The measured downlink data rate reaches up to 390 Mbps at a bandwidth of 60 MHz, which is close to the achievable theoretical value. The average latency both for uplink and downlink was measured to be 19 ms for the round trip time, while the minimum latency value was 6 ms, which is acceptable for many application.

In unlicensed spectrum, a 5G device is required to access to a channel by using load based equipment (LBE) where it does channel sensing whenever it has data to transmit or frame based equipment (FBE) where it only does channel sensing per fixed period. The devices using LBE and FBE can coexist in the 5G network. Therefore, this paper provides a Markov chain model to analyze the system where the LBE devices and the FBE devices coexist. Subsequently, based on channel access time and transmission probability from the Markov chain model, we propose that the devices are able to switch dynamically from FBE to LBE to serve data with high priority such as Ultra-reliable low-latency communication or data with high arrival rate and from LBE to FBE to serve data with low priority such as Enhanced mobile broadband or data with low arrival rate. The numerical results show the benefits of the dynamic switch between LBE and FBE in reducing channel access time for high priority data and energy consumption for low priority data.

The 3rd Generation Partnership Project (3GPP) has defined Ultra-Reliable Low-Latency Communication (URLLC) as one of the main objectives of 5G development to satisfy the applications with stringent requirements of latency and reliability. Uplink (UL) configured-grant (CG) transmission where the user equipment (UE) transmits a packet without scheduling request (SR) and UL grant is standardized by 3GPP Release 15 to reduce latency. The UE also transmits automatically a configured number of repetitions without feedback from the base station (gNB) to increase reliability.Nevertheless, the repetitions are not allowed to transmit outside the hybrid automatic repeat request (HARQ) process containing the first repetition. It might cause a smaller number of transmitted repetitions than configuration that is harmful to the performance of URLLC.This paper uses the reserved resources where the UEs can transmit the repetitions outside the original HARQ process until the configured number is reached. The scheme is developed further when the gNB is equipped with a successive interference cancellation (SIC) receiver so it can decode multiple repetitions of the different UEs in the same reserved resource. The use of reserved resources ensures the performance of UL CG transmission while SIC receiver minimizes the reserved resource's consumption. The numerical results show a higher transmission reliability and lower reserved resource consumption of the proposed scheme compared to the related works.

Ultra-reliable low-latency communication (URLLC) is one of the main services in 5G New Radio (NR) to serve the applications with the strict requirements of latency and reliability. Increase of mobile traffic and bandwidth requirements for new applications have resulted in a shortage of licensed spectrum so that even URLLC services are deemed to be running over the unlicensed spectrum. This may require a significant re-design of channel access, transmission and reception procedures over the unlicensed spectrum and is currently being investigated in The 3rd Generation Partnership Project (3GPP) Release 17.This paper focuses on the channel access mechanism for URLLC services over the unlicensed spectrum. It provides an analytical analysis of current channel access procedures, listen before talk (LBT). LBT states in random duration channel access are modeled through Markov chains which help characterize the closed form expressions for average channel access time. These expressions are evaluated using the parameters from currently standardized channel access priority classes. The evaluation shows the total inability of several current channel access classes to support URLLC services over the unlicensed spectrum even under low load conditions.The insights gained from this analysis lead the proposal of new channel access priority classes where new special classes are introduced for URLLC services. The results are provided demonstrating the improved performance of URLLC services in the unlicensed spectrum with the proposed changes in the channel access procedures.

In uplink (UL) transmission, the Ultra-Reliable Low-Latency Communication (URLLC) users (UEs) might be assigned the grant-free (GF)/configured-grant (CG) periodic resources to transmit data straightaway instead of sending scheduling request (SR) and receiving UL grant. However, when these resources are not in use by the URLLC traffic, the base station (called gNB) can dynamically schedule the Enhanced Mobile Broadband (eMBB) UEs to transmit in the GF resources to increase the resource efficiency. This may lead to potential collision and detrimental QoS for URLLC as some of the URLLC UEs may become active and try to use the same resource assigned to an eMBB UE. In this paper, a two-step strategy containing an overlap indication and explicit Hybrid automatic repeat request (HARQ) feedback is proposed to improve URLLC performance in multiplexing with eMBB. Besides the explicit HARQ feedback structure, a scheme with an additional SR is also presented. Simulation results show that these two schemes help achieving URLLC requirements by reducing error probability due to Demodulation Reference Signal (DMRS) miss-detection while allowing better resource efficiency.

To fulfill the exponential growth of mobile traffic demands, 3GPP has standardized the use of LTE in the 5 GHz unlicensed band in the Release 13 dedicated to LTE Licensed-Assisted Access (LTE-LAA). Simulations and field trials have shown that incumbent WiFi (802.11ac) in the 5 GHz unlicensed band will be the victim in such co-channel deployment with LTE-LAA. Hence a concern is being raised about fair co-existence. In this work, we investigate the limits of Successive Interference Cancellation (SIC) to recover the WiFi packets corrupted by LTE-LAA in the event of a collision. For an indoor deployment, which is the most probable battleground for WiFi and LTE-LAA, we propose a method to perform SIC by using stored clean channel estimates of stronger signals obtained during an interference-free period. Our approach leverages the slow fading channel and hence high coherence time of the indoor channel. For an experimental proof of this phenomenon, we simulated a scenario with interference between 20 MHz 802.11ac and 20 MHz LTE-LAA at different inter-frame-intervals (IFI) of LTE-LAA frames. Our results show that for an LTE-LAA IFI up to 2 milliseconds, the proposed method of using stored channel estimates to perform SIC can achieve significant transmit power gain (TPG) compared to the conventional way of using instantaneous channel estimates. Our method complements the conventional approach to ensure improved WiFi Frame Detection and Decoding while applying SIC. Moreover, our method does not require any coordination between WiFi and LTE-LAA transceivers and hence can be deployed within existing infrastructure with minimal modifications.

Narrowband transmitters such as IEEE 802.15.4 (ZigBee) operating in 2.4 GHz ISM band cause significant degradation of throughput to the co-channel IEEE 802.11g (WiFi). The phenomenon is common in smart factories and smart homes which generously use ZigBee sensors for process monitoring and automation. This interferes with omnipresent WiFi in the same 2.4 GHz ISM band. In our demonstration, we will present Software Defined Radio (SDR) based single antenna and multi-antenna prototype of standard-compliant IEEE 802.11g receiver. Our receiver prototype is capable of significantly reducing the packet error rate while facing multiple co-channel narrowband ZigBee interferers. We also demonstrate a real-time SDR implementation of Soft Bit Maximal Ratio Combiner capable of decoding frames from standard compliant IEEE 802.11g transmitters. This is a first of its kind implementation to the best of author's knowledge. The demonstrations use Ettus B210 as SDR hardware and a combination of signal processing modules from two different SDR packages: GNU Radio and Openairinterface.

The rapid increase in wireless devices and inherent limitation of RF spectrum is causing Co-Channel Interference (CCI). Effects of CCI are prevalent in Industrial Scientific Medical (ISM) bands which lack centralized control over devices operating on heterogeneous standards, a situation entirely different from cellular networks. In this study, we propose physical layer signal processing techniques for multi-antenna OFDM receivers in ISM band for mitigating narrowband CCI. Our work focuses only on receiver side modifications for interoperability with the existing infrastructure. We first analyze two such prominent multi-antenna interference mitigation methods: Optimal Combiner (OC) and Technology-Independent MIMO (TIMO). Optimal Combiner, although theoretically optimal, requires statistics of interferer which is difficult to obtain in practice. TIMO does not benefit from diversity gain despite having two antennas. We propose MLSC (Maximal Ratio Combiner with LLR Scaling) for multi-antenna OFDM receivers which mitigates CCI caused by narrowband interferers as well as benefits from diversity gain. For a given Packet Error Rate (PER), MLSC achieves comparable Transmit Power Gain (TPG) to OC without needing the statistics of the interferer. In addition, MLSC achieves significant TPG compared to TIMO. Further, we propose an improvement to TIMO: DC-TIMO (Diversity Combiner TIMO) which enables it to perform joint interference nulling and diversity combining.

Modern cellular networks are becoming denser, less regularly planned, and increasingly heterogeneous, making performance analysis challenging. We develop a flexible and accurate model of such heterogeneous networks (HetNets) consisting of K tiers of randomly located base stations (BSs), with different densities, transmit powers, and radio access technologies (RATs). Our main goal is to understand the impact of flow level dynamics on such a system, assuming non-saturated users that randomly generate download requests (“flows”). We do so by deriving analytically the per flow delay, the load, the utilization and the congestion probability of BSs in different tiers. We base our analysis on stochastic geometry, to understand the impact of topological randomness and intraand inter-tier interaction, and queueing theory, to model the competition between concurrent flows within the same BS, for each RAT. This allows us to model the interference more realistically as a function of network load. We apply our model to the case of a 2-tier network based on LTE and Wi-Fi and study different user inter-tier association criteria, such as off-load, max-SINR association, and min-delay association. Our results provide some interesting qualitative and quantitative insights about the impact of these association policies and different traffic intensities.

One of the biggest challenges in operating massive multiple-input multiple-output systems is the acquisition of accurate channel state information at the transmitter. To take up this challenge, time division duplex is more favorable thanks to its channel reciprocity between downlink and uplink. However, while the propagation channel over the air is reciprocal, the radio-frequency front-ends in the transceivers are not. Therefore, calibration is required to compensate the RF hardware asymmetry. Although various over-the-air calibration methods exist to address the above problem, this paper offers a unified representation of these algorithms, providing a higher level view on the calibration problem, and introduces innovations on calibration methods. We present a novel family of calibration methods, based on antenna grouping, which improves accuracy and speeds up the calibration process compared to existing methods. We then provide the Cramér-Rao bound as the performance evaluation benchmark and compare maximum likelihood and least squares estimators. We also differentiate between the coherent and non-coherent accumulation of calibration measurements, and point out that enabling non-coherent accumulation allows the training to be spread in time, minimizing the impact to the data service. Overall, these results have special value in allowing the design of reciprocity calibration techniques that are both accurate and resource-effective.

In this paper, we develop a flexible and accurate analytical model of large networks with random base station (BS) placement, in order to understand the impact of key network parameters like BS density and load on the network performance. The main goal is to understand the flow level dynamics of such a system, assuming non-saturated users and studying the congestion statistics for BSs and the per flow delay. To achieve this, we base our analysis on two main tools: (a)stochastic geometry, to understand the impact of topological randomness and coverage maps and (b) queueing theory, to model the competition between concurrent flows within the same BS. Our model is then applied the populars Radio Access Technologies (RATs), such as LTE and WIFi. Our results provide some interesting qualitative and quantitative insights about the performance of those networks.

For time division duplexing (TDD) systems, the physical channel in the air is reciprocal for uplink (UL) and downlink (DL) within the channel coherence time. However when the transceivers' radio frequency (RF) hardware is taken into consideration, TDD channel reciprocity no longer holds because of the non-symmetric characteristics of RF transmit and receive chains. Relative calibration has been proposed to compensate this hardware impairment with a multiplicative matrix. In this paper we perform hardware measurements on this calibration matrix which gives a direct insight on the physical phenomenon of TDD transceivers. Especially, we inspect the assumption that this calibration matrix is diagonal, which is widely adopted in literature but has never been verified by experiments. This work can be regarded as an experimental base for TDD calibration or for theoretical analysis of non-perfect channel reciprocity of TDD systems.

We describe a channel sounding measurement campaign for cellular broadband wireless communications with high speed trains that was carried out in the context of the project CORRIDOR. The campaign combines MIMO and carrier aggregation to achieve very high throughputs. We compare two different scenarios, the first one reflects a cellular deployment, where the base station is about 1km away from the railway line. The second scenario corresponds to a railway deployed network, where the base station is located directly next the railway line. We present the general parameters of the measurement campaign and some results of Power Delay Profiles and Doppler Spectra and their evolution over time. Finally we present a simple channel model that captures the main effects observed in the measurements.

Commoditization and virtualization of wireless networks are changing the economics of mobile networks to help network providers (e.g., MNO, MVNO) move from proprietary and bespoke hardware and software platforms toward an open, cost-effective, and flexible cellular ecosystem. In addition, rich and innovative local services can be efficiently created through cloudification by leveraging the existing infrastructure. In this work, we present RANaaS, which is a cloudified radio access network delivered as a service. RANaaS provides the service life-cycle of an on-demand, elastic, and pay as you go 3GPP RAN instantiated on top of the cloud infrastructure. We demonstrate an example of real-time cloudified LTE network deployment using the OpenAirInterface LTE implementation and OpenStack running on commodity hardware as well as the flexibility and performance of the platform developed.

TV White Spaces (TVWS) technology allows wireless devices to opportunistically use locally-available TV channels enabled by a geolocation database. The UK regulator Ofcom has initiated a pilot of TVWS technology in the UK. This paper concerns a large- scale series of trials under that pilot. The purposes are to test aspects of white space technology, including the white space device and geolocation database interactions, the validity of the channel availability/powers calculations by the database and associated interference effects on primary services, and the performances of the white space devices, among others. An additional key purpose is to perform research investigations such as on aggregation of TVWS resources with conventional resources and also aggregation solely within TVWS, secondary coexistence issues and means to mitigate such issues, and primary coexistence issues under challenging deployment geometries, among others. This paper provides an update on the trials, giving an overview of their objectives and characteristics, some aspects that have been covered, and some early results and observations.

LTE 4G cellular networks are gradually being adopted by all major operators in the world and are expected to rule the cellular landscape at least for the current decade. They will also form the starting point for further progress beyond the current generation of mobile cellular networks to chalk a path towards fifth generation mobile networks. The lack of open cellular ecosystem has limited applied research in this field within the boundaries of vendor and operator R&D groups. Furthermore, several new approaches and technologies are being considered as potential elements making up such a future mobile network, including cloudification of radio network, radio network programability and APIs following SDN principles, native support of machine-type communication, and massive MIMO. Research on these technologies requires realistic and flexible experimentation platforms that offer a wide range of experimentation modes from real-world experimentation to controlled and scalable evaluations while at the same time retaining backward compatibility with current generation systems.

Wireless networks are evolving continuously and expected to provide seamless experience for multiple real-time internet applications. Quality-of-service is one of the major component associated with user experience. In this paper, we have considered the provisioning of desired QoS to mobile users that are capable of running multiple internet applications in parallel. For this purpose, a three-step iterative downlink scheduler is proposed for resource management at per-userper-service level. The scheduler performs sorting in multiple iterations on the basis of three weights. In the first iteration, the scheduler performs sorting based on the throughput weight. The second iteration latency weight and followed by buffer weight in the third iteration. The allocation of resources is done to satisfy the promised QoS to all the services of every user. A comparison is carried out with traditional scheduling algorithms in terms of system throughput, fairness index and percentage of satisfied guaranteed bit-rate users. Results show that the proposed algorithm outperforms existing schemes and the performance is more closer to theoretical system throughput.

Mobile devices have evolved remarkably over the last decade and are now being utilized to access much broader range of internet applications. Moreover, their capability to simultaneously run many applications has significantly transformed the traffic characteristics of mobile networks. Quality of service (QoS) is a fundamental component associated with these applications and network should be able to support multiple QoS requests from the same user at same time. This requires complex buffer management and simultaneous scheduling of resources to multiple users with multiple services. In this paper, we propose a framework with pre-processor for MAC-layer scheduler including two-dimensional buffer management (users × services) that enable more efficient allocation of resources to users running multiple internet applications in parallel. The framework will enhance the performance of existing scheduling algorithms by increasing the resolution of scheduling. A comparative analysis of traditional scheduling algorithms is provided to show the gains of proposed framework.

Ray tracing (RT) is an accurate propagation prediction tool that has been widely used to simulate channel characteristics in indoor environments. To date, the developed RT tool includes not only specular reflection, penetration through dielectric blocks and diffraction, but also diffuse scattering mechanisms. The accuracy, provided by a detailed modeling of the environment, comes at the cost of a high computational complexity, which directly scales with the number of propagation paths considered. We are interested in simulating the radio propagation conditions for a mobile terminal, communicating in a frame based communication system indoors with several fixed nodes. This communication shall be used to obtain the position of the mobile terminal in indoor scenario. Therefore, the correlated temporal and spatial evolution of the channel impulse response is of utmost concern. In this paper, we propose a method to significantly reduce the computational complexity of RT by using a projection of all propagation paths on a subspace spanned by two-dimensional discrete prolate spheroidal (DPS) sequences. With this method the computational complexity can be reduced by more than one order of magnitude for indoor scenarios. The accuracy of our low-complexity DPS subspace based RT algorithm is verified by numeric simulations.

In this paper, we analyze the downlink performance of a multi-user system consisting of mobile users with wide range of velocity. We categorize these users into different groups on the basis of their velocity range and study the impact of feedback delay on each group for closed-loop transmit beamforming. Based on this analysis, we propose an adaptive feedback-scheduling algorithm to minimize the effect of feedback delay on the performance of the system. We derive generalized performance measuring expressions for the proposed algorithm and carry out simulations to validate the analysis.

Multi-user MIMO communication can provide significant gains by exploiting spatial multiplexing. However, it requires better feedback to provide accurate channel state information at the transmitter (CSIT) for minimizing the multiuser interference. 3GPP LTE provides support for MU-MIMO, but it is not sufficient to extract sizable gains. In this paper, our primary goal is to efficiently exploit the system's resources for MU-MIMO in LTE. In the existing 3GPP LTE standard (Rel. 8), we observed that the transmission mode 5 (TM5) dedicated for MU-MIMO utilizes wideband feedback method for providing channel directional information/ precoding matrix indicator (CDI/PMI). The standard supports finer granularity feedback i.e. sub-band feedback method, but it's not utilized for MU-MIMO and restricted only to SU-MIMO. Therefore in this work, we propose to exploit the sub-band feedback for providing more frequent update of PMI. However, in order to support this feedback method, we need to propose a new downlink control information (DCI) format for TM5 that will contain additional fields in comparison to the existing DCI format 1D. Furthermore, to extract optimal performance at the system level, we also propose a MAC-layer scheduling algorithm that deals with resource management on sub-band basis. Utilizing these proposed methods, we show considerable gains in MU-MIMO for 3GPP LTE at the system level.

Relative calibration has been proposed as a simple way to practically exploit the reciprocity of the wireless channel. It is based on a simple convolutional model for the relationship between the channel impulse responses in both directions, and accounts for the discrepancies between transmit and receive radiofrequency components, without the need for specific calibration hardware. However, the relative calibration methods developed so far have been shown to lack robustness with respect to frequency offset between the devices on both sides of the considered channel. In this article, we introduce a relative calibration algorithm that properly deals with the presence of frequency offset. We verify its robustness and assess its performance through simulations, and validate experimentally the proposed model on measured channels.

Most of the recent wireless communication systems are interference limited rather than noise limited. In the case of a very strong interferer the conventional assumption of the interference as Gaussian is extremely suboptimal. However optimal (capacity achieving) receivers utilize some prior knowledge about the interference to reach optimality. The link abstraction for such receiver structures is not studied well. We investigate how the conventional mutual information based link abstraction technique can be extended for the accurate and efficient link performance modeling for low complexity optimal receivers. So, in this paper we propose a mutual information based link abstraction methodology of an optimal, low complexity interference aware receiver for multi-user MIMO in the frame work of LTE. For the sake of comparison we performed abstraction of interference aware receiver with Exponential Effective SINR Mapping (EESM) method as well. We show with the help of results that our proposed method outperforms the EESM and provides the system level with more accurate link quality metric.

The use of distributed space-time codes in cooperative communications promises to increase the rate and reliability of data transmission. These gains were mostly demonstrated for ideal scenarios, where all nodes are perfectly synchronized. Considering a cooperative uplink scenario with asynchronous nodes, the system suffers from two effects: timing errors and individual carrier frequency offsets. In effect, timing errors can completely cancel the advantages introduced by space-time codes, while individual carrier frequency offsets provide a great challenge to receivers. Indeed, frequency offsets are perceived as a time-variant channel (even if the individual links are static) in distributed cooperative communications. We show that using OFDM, space-time codes (STCs) become tolerant to timing errors. Channel estimation and tracking takes care of frequency offsets. Our simulations demonstrate that the bit error rate performance improves by an order of magnitude, when using a cooperative system design, which takes these two effects into account.

This paper focuses on the performance of LTE in rural areas which is based on a channel measurement campaign conducted with the Eurecom OpenAirInterface LTE testbed at 800MHz. This testbed is based on LTE release 8 PHY layer and implements transmission modes 1 (single antenna - SISO), 2 (transmit diversity), and 6 (single-user MIMO - closed loop rank-1 precoding) in real time. In addition to the throughput recorded from the real modem, the raw channel estimates were stored and used for extrapolating the performance to transmission mode 5 (multi-user MIMO). This extrapolation is done by means of a mutual-information based link-quality model that abstracts the performance of multi-user (MU) MIMO for an interference aware receiver proposed by Ghaffar et al and then the results are compared with the performance of abstraction to transmission mode 2 and 6. The superior performance of MU MIMO mode (with interference aware receiver) over other transmission modes is illustrated and it is shown that if the channel admits then MU MIMO is the preferred option.

In order to maximize the system throughput, future wireless communication systems will employ a very tight frequency reuse. This leads to interference limited systems where the interference is high at the cell edges. The key ingredient to such networks are thus receivers that are able to exploit the structure of this interference instead of nulling or attenuating it. In this paper we apply such a receiver structure to a distributed multiple-input multiple-output (MIMO) scenario to decode two independent data streams from two synchronized base stations. Further we show how the distributed MIMO receiver is implemented in real-time on the OpenAirInterface platform and provide results from field trials and compare them to the simulation results. Applications of the distributed MIMO receiver include single-frequency cellular as well as mesh networks. OpenAirInterface is an experimental open-source real-time hardware and software platform for experimentation in wireless communications and signal processing. Its current implementation provides a full software modem comprising physical and link layer functionalities for cellular and mesh network topologies.

In this paper, an empirical model of the indoor distributed channel is presented. In particular, the shadowing and fading statistics are extracted from experimental data at 2.45 GHz in stationary and mobile scenarios. Highlights of the paper include a separate model for static and dynamic shadowing, a model for shadowing correlation, as well as a single analytical distribution of small-scale fading for various types of indoor node mobility.

In this work we study the capacity of multi-user multiple-input multiple-output (MU-MIMO) downlink channels with codebook-based limited feedback using real measurement data. Several aspects of MU-MIMO channels are evaluated. Firstly, we compare the sum rate of different MU-MIMO precoding schemes in various channel conditions. Secondly, we study the effect of different codebooks on the performance of limited feedback MU-MIMO. Thirdly, we relate the required feedback rate with the achievable rate on the downlink channel. Real multi-user channel measurement data acquired with the Eurecom MIMO OpenAir Sounder (EMOS) is used. To the best of our knowledge, these are the first measurement results giving evidence of how MU-MIMO precoding schemes depend on the precoding scheme, channel characteristics, user separation, and codebook. For example, we show that having a large user separation as well as codebooks adapted to the second order statistics of the channel gives a sum rate close to the theoretical limit. A small user separation due to bad scheduling or a poorly adapted codebook on the other hand can impair the gain brought by MU-MIMO. The tools and the analysis presented in this paper allow the system designer to trade-off downlink rate with feedback rate by carefully choosing the codebook.

In multi-user multiple-input multiple-output (MU-MIMO) systems, channel state information at the transmitter (CSIT) allows for multi-user spatial multiplexing and thus increases the system throughput. We assume that CSIT is obtained by means of a finite-rate feedback channel through channel vector quantization (CVQ) at the receiver. In this paper we use real channel measurements to study the effect of CVQ on the sum rate of a MU-MIMO system employing linear precoding. The measurement data has been acquired using Eurecom's MIMO Openair Sounder (EMOS). The EMOS can perform realtime MIMO channel measurements synchronously over multiple users. We consider CVQ using a Fourier codebook, a random codebook and a random codebook exploiting the second order statistics of the channel. For comparison, we also show the capacity of a single-user system using time division multiple access (TDMA) with no CSIT at all. The results show that the Fourier codebook shows very poor performance in the measured channels. Random codebooks - although suboptimal - provide a much better performance in the measured channels.

In multi-user multiple-input multiple-output (MU-MIMO) systems, spatial multiplexing can be employed to increase the throughput without the need for multiple antennas and expensive signal processing at the user equipments. In theory, MU-MIMO is also more immune to most of propagation limitations plaguing single-user MIMO (SU-MIMO) systems, such as channel rank loss or antenna correlation. However, in this paper we show that this is not always true. We compare the capacity and the correlation of measured MU-MIMO channels for both outdoor and indoor scenarios. The measurement data has been acquired using Eurecompsilas MIMO openair sounder (EMOS). The EMOS can perform real-time MIMO channel measurements synchronously over multiple users. The results show that in most scenarios MU-MIMO provides a higher throughput than SU-MIMO also in the measured channels. However, in outdoor scenarios with a line of sight, the capacity drops significantly when the users are close together, due to high correlation at the transmitter side of the channel. In such a case, the performance of SU-MIMO and MU-MIMO is comparable.

The throughput of the high speed downlink packet access (HSDPA) sub-system of UMTS suffers significantly from multiple access interference in the wireless channel. A linear minimum mean square error (LMMSE) equalizer at the receiver achieves higher throughput than a conventional RAKE receiver, at the cost of higher complexity. We introduce an iterative algorithm based on Krylov subspace projections, approximating the LMMSE equalizer with negligible loss of performance for the receiver. Slow variations of the channel can be exploited to allow further acceleration of the algorithm. Computational complexity as well as storage requirements are strongly reduced