72 research outputs found
Cognitive-Based Solutions to Spectrum Issues in Future Satellite Communication Systems
With particular attention to Satellite Communications (SatComs), cognitive-based solutions are investigated. With cognitive-based solutions we refer to all those techniques that aim at improving spectrum utilization of the available spectrum and rely on the knowledge of the environment in which the systems operate. As a matter of fact, an improved spectrum utilization enables higher throughput capacities that will satisfy the future markets and demands of an increasingly connected world.
Throughout the thesis, several techniques are proposed, developed, and assessed with respect to specific scenarios of interest. Particular focus has been put on spectrum awareness techniques for system coexistence, and on spectrum exploitation techniques for an improved efficiency in terms of resource utilization
Matching Traffic Demand in GEO Multibeam Satellites: The Joint Use of Dynamic Beamforming and Precoding Under Practical Constraints
To adjust for the non-uniform spatiotemporal nature of traffic patterns, next-generation high throughput satellite (HTS) systems can benefit from recent technological advancements in the space-segment in order to dynamically design traffic-adaptive beam layout plans (ABLPs). In this work, we propose a framework for dynamic beamforming (DBF) optimization and adaptation in dynamic environments. Given realistic traffic patterns and a limited power budget, we propose a feasible DBF operation for a geostationary multibeam HTS network. The goal is to minimize the mismatch between the traffic demand and the offered capacity under practical constraints. These constraints are dictated by the traffic-aware design requirements, the on-board antenna system limitations, and the signaling considerations in the K-band. Noting that the ABLP is agnostic about the inherent inter-beam interference (IBI), we construct an interference simulation environment using irregularly shaped beams for a large-scale multibeam HTS system. To cope with IBI, the combination of on-board DBF and on-ground precoding is considered. For precoded and non-precoded HTS configurations, the proposed design shows better traffic-matching capabilities in comparison to a regular beam layout plan. Lastly, we provide trade-off analyses between system-level key performance indicators for different realistic non-uniform traffic patterns
Demand-based optimization for adaptive multi-beam satellite communication systems
Satellite operators use multiple spot beams of high throughput satellite systems to provide internet services to broadband users. However, in recent years, new mobile broadband users with diverse demand requisites are growing, and satellite operators are obliged to provide services agreed in the Service Level Agreements(SLA) to remote rural locations, mid-air aeroplanes and mid-ocean ships. Furthermore, the expected demand is spatio-temporal which varies along the geographical location of the mobile users with time and hence, creating more dynamic, non uniformly distributed, and time sensitive demand profiles. However, the current satellite systems are only designed to perform similarly irrespective of the changes in demand profiles. Hence, a practical approach to meet such heterogeneous demand is to design adaptive systems by exploiting the advancements in recently developed technologies such as precoding, active antenna array, digital beamforming networks, digital transparent payload and onboard signal processing.
Accordingly, in this work, we investigate and develop advanced demand-based resource optimization modules that fit future payload capabilities and satisfy the satellite operators’ interests. Furthermore, instead of boosting the satellite throughput (capacity maximization), the goal is to optimize the available resources such that the satellite offered capacity on the ground continuously matches the geographic distribution of the traffic demand and follows its variations in time. However, we can introduce adaptability at multiple levels of the transmission chain of the satellite system, either with long term flexibility (optimization over frequency, time, power, beam pattern and footprint) or short term flexibility (optimization over user scheduling). These techniques can be optimized as either standalone or in parallel or even jointly for maximum demand satisfaction. However, in the scope of this thesis, we have designed real time optimizations only for some of the radio resource schemes.
Firstly, we explore beam densification, where by increasing the number of beams, we improve the antenna gain values at the high demand hot-spot regions. However, such increase in the number of beams also increase the interbeam interference and badly affects SINR performance. Hence, in the first part of Chapter 2 of this thesis, we focus on finding an optimal number of beams for given high demand hot-spot region of a demand distribution profile. Also, steering the beams towards high demand regions, further increase the demand satisfaction. However, the positioning of the beams need to be carefully planned. On one hand, closely placed beams result in poor SINR performance. On the other hand, beams that are placed far away will have poor antenna gain values for the users away from the beam centers. Hence, in the second part of Chapter 2, we focus on finding optimized beam positions for maximum demand satisfaction in high demand hot-spot regions. Also, we propose a dynamic frequency-color coding strategy for efficient spectrum and interference management in demand-driven adaptive systems.
Another solution is the proposed so-called Adaptive Multi-beam Pattern and Footprint (AMPF) design, where we fix the number of beams and based on the demand profile, we configure adaptive beam shapes and sizes along with their positions. Such an approach shall distribute the total demand across all the beams more evenly avoiding overloaded or underused beams. Such optimization was attempted in Chapter 3 using cluster analysis.
Furthermore, demand satisfaction at both beam and user level was achieved by carefully performing demand driven user scheduling. On one hand, scheduling most orthogonal users at the same time may yield better capacity but may not provide demand satisfaction. This is majorly because users with high demand need to be scheduled more often in comparison to users with low demand irrespective of channel orthogonality. On the other hand, scheduling users with high demand which are least orthogonal, create strong interbeam interference and affect precoding performance. Accordingly, two demand driven scheduling algorithms (Weighted Semi-orthogonal scheduling (WSOS) and Interference-aware demand-based user scheduling) are discussed in Chapter 4.
Lastly, in Chapter 5, we verified the impact of parallel implementation of two different demand based optimization techniques such as AMPF design and WSOS user scheduling. Evidently, numerical results presented throughout this thesis validate the effectiveness of the proposed demand based optimization techniques in terms of demand matching performance compared to the conventional non-demand based approaches
Mobile Cell-Free Massive MIMO: Challenges, Solutions, and Future Directions
Cell-free (CF) massive multiple-input multiple-output (MIMO) systems, which
exploit many geographically distributed access points to coherently serve user
equipments via spatial multiplexing on the same time-frequency resource, has
become a vital component of the next-generation mobile communication networks.
Theoretically, CF massive MIMO systems have many advantages, such as large
capacity, great coverage, and high reliability, but several obstacles must be
overcome. In this article, we study the paradigm of CF massive MIMO-aided
mobile communications, including the main application scenarios and associated
deployment architectures. Furthermore, we thoroughly investigate the challenges
of CF massive MIMO-aided mobile communications. We then exploit a novel
predictor antenna, hierarchical cancellation, rate-splitting and dynamic
clustering system for CF massive MIMO. Finally, several important research
directions regarding CF massive MIMO for mobile communications are presented to
facilitate further investigation.Comment: 9 pages, 4 figures, 2 tables, accepted by IEEE Wireless
Communications Magazin
Rate-splitting multiple access for non-terrestrial communication and sensing networks
Rate-splitting multiple access (RSMA) has emerged as a powerful and flexible
non-orthogonal transmission, multiple access (MA) and interference management
scheme for future wireless networks. This thesis is concerned with the application of
RSMA to non-terrestrial communication and sensing networks. Various scenarios
and algorithms are presented and evaluated.
First, we investigate a novel multigroup/multibeam multicast beamforming strategy
based on RSMA in both terrestrial multigroup multicast and multibeam satellite
systems with imperfect channel state information at the transmitter (CSIT). The
max-min fairness (MMF)-degree of freedom (DoF) of RSMA is derived and shown
to provide gains compared with the conventional strategy. The MMF beamforming
optimization problem is formulated and solved using the weighted minimum mean
square error (WMMSE) algorithm. Physical layer design and link-level simulations
are also investigated. RSMA is demonstrated to be very promising for multigroup
multicast and multibeam satellite systems taking into account CSIT uncertainty
and practical challenges in multibeam satellite systems.
Next, we extend the scope of research from multibeam satellite systems to satellite-
terrestrial integrated networks (STINs). Two RSMA-based STIN schemes are
investigated, namely the coordinated scheme relying on CSI sharing and the co-
operative scheme relying on CSI and data sharing. Joint beamforming algorithms
are proposed based on the successive convex approximation (SCA) approach to
optimize the beamforming to achieve MMF amongst all users. The effectiveness and
robustness of the proposed RSMA schemes for STINs are demonstrated.
Finally, we consider RSMA for a multi-antenna integrated sensing and communications (ISAC) system, which simultaneously serves multiple communication users
and estimates the parameters of a moving target. Simulation results demonstrate
that RSMA is beneficial to both terrestrial and multibeam satellite ISAC systems by
evaluating the trade-off between communication MMF rate and sensing Cramer-Rao
bound (CRB).Open Acces
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