Ramoni Adeogun

• PhD, BEng
• Professor (Associate) at Aalborg University

Short-range low-power 6th generation (6G) in-X subnetworks are proposed as a viable radio concept for supporting extreme communication requirements in emerging applications such as wireless control of robotic arms and control of critical on-body devices, e.g. wireless heart pacemaker. For these applications, ultra-high reliability (e.g., above 6 ni...

5G communication systems are one of the major enabling technologies to meet the needs of Industry 4.0. This paper focuses on the use case of automated guided vehicles (AGVs) in an outdoor industrial scenario. To meet the communication requirements in these type of use cases, dual connectivity (DC) with resource aggregation in the uplink (UL) is gen...

This paper proposes a distributed deep reinforcement learning (DRL) methodology for autonomous mobile robots (AMRs) to manage radio resources in an indoor factory with no network infrastructure. Hence, deep neural networks (DNN) are used to optimize the decision policy of the robots, which will make decisions in a distributed manner without signali...

The 6th Generation (6G) radio access technology is expected to support extreme communication requirements in terms of throughput, latency and reliability, which can only be achieved by providing capillary wireless coverage. In this paper, we present our vision for short-range low power 6G ‘in-X’ subnetworks, with the ‘X’ standing for the entity in...

The deployment of relays between Internet of Things (IoT) end devices and gateways can improve link quality. In cellular-based IoT, relays have the potential to reduce base station overload. The energy expended in single-hop long-range communication can be reduced if relays listen to transmissions of end devices and forward these observations to ga...

Recently, 6G in-X subnetworks have been proposed as low-power short-range radio cells to support localized extreme wireless connectivity inside entities such as industrial robots, vehicles, and the human body. Deployment of in-X subnetworks within these entities may result in rapid changes in interference levels and thus, varying link quality. This...

In this paper, we develop a novel power control solution for subnetworks-enabled distributed control systems in factory settings. We propose a channel-independent control-aware (CICA) policy based on the logistic model and learn the parameters using Bayesian optimization with a multi-objective tree-structured Parzen estimator. The objective is to m...

Transmit power control (TPC) is a key mechanism for managing interference, energy utilization, and connectivity in wireless systems. In this paper, we propose a simple low-complexity TPC algorithm based on the deep unfolding of the iterative projected gradient descent (PGD) algorithm into layers of a deep neural network and learning the step-size p...

Future wireless systems are expected to support mission-critical services demanding higher and higher reliability. In this letter, we dimension the radio resources needed to achieve a given failure probability target for ultra-reliable wireless systems in high interference conditions, assuming a protocol with frequency hopping combined with packet...

In-X subnetworks are expected to be located at the very edge of the 6G 'network of networks' and provide localized wireless connectivity for in-vehicle, in-robot, in-body communication. By nature in-X subnetworks can lead to dense crowds, calling for efficient radio resource management techniques. In this article, we introduce a hybrid radio resour...

Future wireless systems are expected to support mission-critical services demanding higher and higher reliability. In this letter, we dimension the radio resources needed to achieve a given failure probability target for ultra-reliable wireless systems in high interference conditions, assuming a protocol with frequency hopping combined with packet...

6th Generation (6G) industrial wireless subnetworks are expected to replace wired connectivity for control operation in robots and production modules. Interference management techniques such as centralized power control can improve spectral efficiency in dense deployments of such subnetworks. However, existing solutions for centralized power contro...

In this paper, we investigate dynamic resource selection in dense deployments of the recent 6G mobile in-X subnetworks (inXSs). We cast resource selection in inXSs as a multi-objective optimization problem involving maximization of the minimum capacity per inXS while minimizing overhead from intra-subnetwork signaling. Since inXSs are expected to b...

In this letter, we investigate dynamic resource selection in dense deployments of a recent 6G mobile in-X subnetworks (inXSs). We cast resource selection in inXSs as a multi-objective optimization problem involving maximization of per inXS sum capacities. Since inXSs are expected to be autonomous, selection decisions are made by each inXS based on...

In this letter, we investigate dynamic resource selection in dense deployments of a recent 6G mobile in-X subnetworks (inXSs). We cast resource selection in inXSs as a multi-objective optimization problem involving maximization of per inXS sum capacities. Since inXSs are expected to be autonomous, selection decisions are made by each inXS based on...

A polarimetric model for the power delay spectrum for inroom communication is proposed. The proposed model describes the gradual depolarization of the signal with delay. The model is based on the theory of room electromagnetics, specifically the mirror source approach, which is straightforwardly generalized to the polarimetric case. Compared to the...

We propose a multivariate log-normal distribution to jointly model received power, mean delay, and root mean square (rms) delay spread of wideband radio channels, referred to as the standardized temporal moments. The model is validated using experimental data collected from five different measurement campaigns (four indoor and one outdoor scenario)...

This article presents an overview of current Industry 4.0 applied research topics, addressed from both the industrial production and wireless communication points of view. A roadmap toward achieving the more advanced industrial manufacturing visions and concepts, such as “swarm production” (nonlinear and fully decentralized production) is defined,...

The continuous proliferation of applications requiring wireless connectivity will eventually result in latency and reliability requirements beyond what is achievable with current technologies. Such applications can for example include industrial control at the sensor-actuator level, intra-vehicle communication , fast closed loop control in intra-bo...

We propose a multivariate log-normal distribution to jointly model received power, mean delay, and root mean square (rms) delay spread of wideband radio channels, referred to as the standardized temporal moments. The model is validated using experimental data collected from five different measurement campaigns (four indoor and one outdoor scenario)...

Estimating parameters of stochastic radio channel models based on new measurement data is an arduous task usually involving multiple steps such as multipath extraction and clustering. We propose two different machine learning methods, one based on approximate Bayesian computation (ABC) and the other on deep learning, for fitting data to stochastic...

Estimating parameters of stochastic radio channel models based on new measurement data is an arduous task usually involving multiple steps such as multipath extraction and clustering. We propose two different machine learning methods, one based on approximate Bayesian computation (ABC) and the other on deep learning, for fitting data to stochastic...

Short range low power 6th Generation (6G) wireless subnetworks can support life critical services like engine and break control in intra-vehicle scenarios, or intra-body heart-rate control. Such services may target communication cycles below 0.1 ms and a wired-like reliability, translating to a multi-GHz spectrum demand in case of dense deployments...

Metropolitan cities often experience waste collection challenges due to ineffective methods of collection. This paper described criteria and an approach for efficient decision-making for waste collection that will make use of data generated by IoT-enabled objects. This implies taking into account multi-objective goals in the collection process whil...

This letter proposes a machine learning based method for the calibration of stochastic radio propagation models. Model calibration is cast as a regression problem involving mapping of the channel transfer function or impulse response to the model parameters. A multilayer perceptron is trained with summary statistics computed from synthetically gene...

This paper generalizes a propagation graph model to polarized indoor wireless channels. In the original contribution, the channel is modelled as a propagation graph in which vertices represent transmitters, receivers and scatterers while edges represents the propagation conditions between vertices. Each edge is characterized by an edge transfer fun...

This paper presents a reduced complexity method for computing the transfer matrix of wireless channels in complex indoor environments with a large number of rooms using propagation graphs. Multi-room indoor environments can be represented in a vector signal flow graph with rooms in the complex structure as nodes and propagation between rooms as bra...

Hybrid heterogeneous wireless networks utilizing both traditional microwave frequency band and millimetre wave band are currently been investigated as a potential approach to meet the increasing demand for ultra-high rate transmission with the severe microwave spectrum scarcity and requirement for low power network devices. In this paper, we invest...

A method for resource allocation in dual band HETNETs is presented in this talk.

This presentation summarizes my paper on asumptotic perfomance bound on estimation, interpolation and prediction of MIMO-OFDM wireless channels. Simple closed form expressions relating the estimation/prediction error to system parameters are given in this talk.

A model for polarized wireless channels based on propagation graphs is presented in this talk with applications to dual polarized MIMO channels

Metropolitan cities often experience waste collection challenges due to ineffective methods of collection. This paper described criteria and an approach for efficient decision-making for waste collection that will make use of data generated by IoT-enabled objects. This implies taking into account multi-objective goals in the collection process whil...

This paper investigates the prediction of MIMO narrowband multipath fading channels for mobile-to-mobile wireless communication systems. Using a statistical model for mobile-tomobile communication in urban and suburban environments, we derive a parameterized double directional model and utilize a multidimensional extension of the ESPRIT algorithm t...

In this paper, we investigated the capacity and bit error rate (BER) performance of Multiple Input Multiple Output (MIMO) satellite systems with single and multiple dual polarized satellites in geostationary orbit and a mobile ground receiving station with multiple antennas. We evaluated the effects of both system parameters such as number of satel...

In this paper, we investigate methods for interference location in satellite communication system using satellite multi-beam antenna with subspace based schemes. A novel MUSIC based approach is proposed for estimating the direction of arrival of the interfering sources. The proposed method provides super resolution and asymptotic maximum likelihood...

Information on the future state of time varying frequency selective channels can significantly enhance the effectiveness of feedback in adaptive and limited feedback MIMO-OFDM systems. This paper investigates the parametric extrapolation of wideband MIMO channels using variations of the double directional MIMO model. We propose three predictors whi...

In this paper, we derive an asymptotic closed--form expression for the error bound on extrapolation of doubly selective mobile MIMO wireless channels. The bound shows the relationship between the prediction error and system design parameters such as bandwidth, number of antenna elements, and number of frequency and temporal pilots, thereby providin...

We investigate the prediction of wideband MIMO spatial channels. We propose a two-stage long range parametric prediction scheme that exploits the temporal, spatial and frequency correlations in a realistic cluster based fading channel. The proposed scheme utilizes the frequency correlation in an ESPRIT-like approach to estimate the cluster delays a...

A novel prediction scheme for polarized narrowband MIMO channels is proposed in this paper. The prediction scheme is based on estimation of the parameters of a double directional polarized propagation model. The proposed algorithm transforms the channel impulse response matrix in such a manner that a multidimensional extension of the ESPRIT algorit...

In this paper, we investigate the estimation of multipath parameters and prediction of wideband multipath fading channels for mobile-to-mobile wireless communications. Based on a statistical model for mobile to mobile urban and suburban channels, we derive a parametrized model and utilize two-dimensional ESPRIT algorithm to jointly estimate the del...

This paper investigates the prediction of single input single output (SISO) narrowband multipath fading channels for mobile-to-mobile wireless communications. Using a statistical model for mobile to mobile urban and suburban channels, we derive a parametrized model and utilize the ESPRIT algorithm to extract the effective Doppler frequencies from n...

A novel subspace based joint angle of arrival (AOA), angles of departure (AOD), Doppler shifts and polarization states parameter estimation scheme for polarized two-dimensional (2D) double directional MIMO multipath channels is proposed in this paper. A narrowband system with non-polarized uniform linear array at the transmitter and cross-polarized...

In this paper, we propose a novel long range prediction scheme for narrowband MIMO systems using realistic spatial channel model. The algorithm exploits both the temporal and spatial structure of the MIMO channel to jointly estimate the multipath parameters via a subspace based three dimensional ESPRIT approach. We propose simple transformations to...

In this paper, we propose an ESPRIT-based parametric prediction scheme for narrowband MIMO systems that fully exploits both temporal and spatial correlations in realistic MIMO channels. The proposed predictor uses a vector transmit spatial signature model and two-dimensional ESPRIT for the estimation of the channel parameters. The proposed scheme o...

Satellite formation flying is an essential capability for many space missions that allow several closely spaced smaller satellites to be deployed. Depending on mission requirements, the ground receive station may carry several antennas and receive signal from each of the satellites in order to increase capacity and QoS. In this paper, we proposed a...