Two-tier User Association and Resource Allocation Design for Integrated Satellite-Terrestrial Networks

in ICC Workshop on Mega-Constellations in the 6G Era (6gsatcomnet), Rome, Italy, May 2023. (2023)

Demand-aware Flexible Handover Strategy for LEO Constellation

in ICC Workshop on Mega-Constellations in the 6G Era (6gsatcomnet), Rome, Italy, May 2023. (2023)

GEO Payload Power Minimization: Joint Precoding and Beam Hopping Design

in Proceedings of IEEE Global Communications Conference GLOBECOM 2022 (2022, December 05)

This paper aims to determine linear precoding (LP) vectors, beam hopping (BH), and discrete DVB-S2X transmission rates jointly for the GEO satellite communication systems to minimize the payload power ... [more ▼]

This paper aims to determine linear precoding (LP) vectors, beam hopping (BH), and discrete DVB-S2X transmission rates jointly for the GEO satellite communication systems to minimize the payload power consumption and satisfy ground users’ demands within a time window. Regarding constraint on the maximum number of illuminated beams per time slot, the technical requirement is formulated as a sparse optimization problem in which the hardware-related beam illumination energy is modeled in a sparsity form of the LP vectors. To cope with this problem, the compressed sensing method is employed to transform the sparsity parts into the quadratic form of precoders. Then, an iterative window-based algorithm is developed to update the LP vectors sequentially to an efficient solution. Additionally, two other two-phase frameworks are also proposed for comparison purposes. In the first phase, these methods aim to determine the MODCOD transmission schemes for users to meet their demands by using a heuristic approach or DNN tool. In the second phase, the LP vectors of each time slot will be optimized separately based on the determined MODCOD schemes. [less ▲]

Non-Coherent Massive MIMO Integration in Satellite Communication

Scientific Conference (2022, October)

Massive Multiple Input-Multiple Output (mMIMO) technique has been considered an efficient standard to improve the transmission rate significantly for the following wireless communication systems, such as ... [more ▼]

Massive Multiple Input-Multiple Output (mMIMO) technique has been considered an efficient standard to improve the transmission rate significantly for the following wireless communication systems, such as 5G and beyond. However, implementing this technology has been facing a critical issue of acquiring much channel state information. Primarily, this problem becomes more criticising in the integrated satellite and terrestrial networks (3GPP-Release 15) due to the countable high transmission delay. To deal with this challenging problem, the mMIMO-empowered non-coherent technique can be a promising solution. To our best knowledge, this paper is the first work considering employing the non-coherent mMIMO in satellite communication systems. This work aims to analyse the challenges and opportunities emerging with this integration. Moreover, we identified the issues in this conjunction. The preliminary results presented in this work show that the performance measured in bit error rate (BER) and the number of antennas are not far from that required for terrestrial links. Furthermore, thanks to mMIMO in conjunction with the non-coherent approach, we can work in a low signal-to-noise ratio (SNR) regime, which is an excellent advantage for satellite links. [less ▲]

The Next Generation of Beam Hopping Satellite Systems: Dynamic Beam Illumination with Selective Precoding

in IEEE Transactions on Wireless Communications (2022)

Combining Time-Flexible Satellite Payload with Precoding: The Cluster Hopping Approach

in IEEE Transactions on Vehicular Technology (2022)

High throughput geostationary (GEO) satellite systems are characterized by a multi-beam wide coverage. However, developing efficient resource management mechanisms to meet the heterogeneous user traffic ... [more ▼]

High throughput geostationary (GEO) satellite systems are characterized by a multi-beam wide coverage. However, developing efficient resource management mechanisms to meet the heterogeneous user traffic demands remains an open challenge for satellite operators. Furthermore, the spectrum shortage and the ever increasing demands claim for more aggressive frequency reuse. In this paper, we combine the time-flexible payload capabilities known as beam hopping (BH) with precoding techniques in order to satisfy user traffic requests in areas of high demand (i.e. hot-spot areas). The proposed framework considers a flexible beam-cluster hopping where adjacent beams can be activated if needed, forming clusters with various shapes and sizes. In this context, we present three strategies to design the beam illumination patterns. First, a max-min user demand fairness satisfaction problem; second, a penalty-based optimization is considered to penalize the occurrence of adjacent beams in an attempt to avoid precoding whenever possible. Third, seeking a low-complexity design, we propose a queuing-based approach to solve the problem in a time-slot by time-slot basis trying to provide service to users based on the requested demands. The three methods are discussed in detailed and evaluated via numerical simulations, confirming their effectiveness versus benchmark schemes and identifying the pros and cons of each proposed design. [less ▲]

Joint Radio Resource Management and Link Adaptation for Multicasting 802.11ax-based WLAN Systems

in IEEE Transactions on Wireless Communications (2021)

Adopting OFDMA and MU-MIMO techniques for both downlink and uplink IEEE 802.11ax will help next-generation WLANs efficiently cope with large numbers of devices but will also raise some research challenges ... [more ▼]

Adopting OFDMA and MU-MIMO techniques for both downlink and uplink IEEE 802.11ax will help next-generation WLANs efficiently cope with large numbers of devices but will also raise some research challenges. One of these is how to optimize the channelization, resource allocation, beamforming design, and MCS selection jointly for IEEE 802.11ax-based WLANs. In this paper, this technical requirement is formulated as a mixed-integer non-linear programming problem maximizing the total system throughput for the WLANs consisting of unicast users with multicast groups. A novel two-stage solution approach is proposed to solve this challenging problem. The first stage aims to determine the precoding vectors under unit-power constraints. These temporary precoders help re-form the main problem into a joint power and radio resource allocation one. Then, two low-complexity algorithms are proposed to cope with the new problem in stage two. The first is developed based on the well-known compressed sensing method while the second seeks to optimize each of the optimizing variables alternatively until reaching converged outcomes. The outcomes corresponding to the two stages are then integrated to achieve the complete solution. Numerical results are provided to confirm the superior performance of the proposed algorithms over benchmarks. [less ▲]

RSSI-Based Hybrid Beamforming Design with Deep Learning

in 2020 IEEE International Conference on Communications Proceedings (2020, June 07)

Hybrid beamforming is a promising technology for 5G millimetre-wave communications. However, its implementation is challenging in practical multiple-input multiple-output (MIMO) systems because non-convex ... [more ▼]

Hybrid beamforming is a promising technology for 5G millimetre-wave communications. However, its implementation is challenging in practical multiple-input multiple-output (MIMO) systems because non-convex optimization problems have to be solved, introducing additional latency and energy consumption. In addition, the channel-state information (CSI) must be either estimated from pilot signals or fed back through dedicated channels, introducing a large signaling overhead. In this paper, a hybrid precoder is designed based only on received signal strength indicator (RSSI) feedback from each user. A deep learning method is proposed to perform the associated optimization with reasonable complexity. Results demonstrate that the obtained sum-rates are very close to the ones obtained with full-CSI optimal but complex solutions. Finally, the proposed solution allows to greatly increase the spectral efficiency of the system when compared to existing techniques, as minimal CSI feedback is required. [less ▲]

Admission Control and Network Slicing for Multi-Numerology 5G Wireless Networks

in IEEE Networking Letters (2020)

This letter studies the admission control and network slicing design for 5G New Radio (5G-NR) systems in which the total bandwidth is sliced to support the enhanced mobile broadband (eMBB) and ultra ... [more ▼]

This letter studies the admission control and network slicing design for 5G New Radio (5G-NR) systems in which the total bandwidth is sliced to support the enhanced mobile broadband (eMBB) and ultra reliable and low latency communication (URLLC) services. We allow traffic from the eMBB bandwidth part to be overflowed to the URLLC bandwidth part in a controlled manner. We develop a mathematical framework to analyze the blocking probabilities of both eMBB and URLLC services based on which the network slicing and admission control is jointly optimized to minimize the blocking probability of the eMBB traffic subject to the blocking probability constraint for the URLLC traffic. An efficient iterative algorithm is proposed to deal with the underlying problem. [less ▲]

Joint Data Compression and Computation Offloading in Hierarchical Fog-Cloud Systems

in IEEE Transactions on Wireless Communications (2019)

Data compression (DC) has the potential to significantly improve the computation offloading performance in hierarchical fog-cloud systems. However, it remains unknown how to optimally determine the ... [more ▼]

Data compression (DC) has the potential to significantly improve the computation offloading performance in hierarchical fog-cloud systems. However, it remains unknown how to optimally determine the compression ratio jointly with the computation offloading decisions and the resource allocation. This optimization problem is studied in this paper where we aim to minimize the maximum weighted energy and service delay cost (WEDC) of all users. First, we consider a scenario where DC is performed only at the mobile users. We prove that the optimal offloading decisions have a threshold structure. Moreover, a novel three-step approach employing convexification techniques is developed to optimize the compression ratios and the resource allocation. Then, we address the more general design where DC is performed at both the mobile users and the fog server. We propose three algorithms to overcome the strong coupling between the offloading decisions and the resource allocation. Numerical results show that the proposed optimal algorithm for DC at only the mobile users can reduce the WEDC by up to 65% compared to computation offloading strategies that do not leverage DC or use sub-optimal optimization approaches. The proposed algorithms with additional DC at the fog server lead to a further reduction of the WEDC. [less ▲]