JOINT CARRIER ALLOCATION AND PRECODING OPTIMIZATION FOR INTERFERENCE-LIMITED GEO SATELLITE

Scientific Conference (2022)

The rise of flexible payloads on satellites opens a door for controlling satellite resources according to the user demand, user location, and satellite position. In addition to resource management ... [more ▼]

The rise of flexible payloads on satellites opens a door for controlling satellite resources according to the user demand, user location, and satellite position. In addition to resource management, applying precoding on flexible payloads is essential to obtain high spectral efficiency. However, these cannot be achieved using a conventional resource allocation algorithm that does not consider the user demand. In this paper, we propose a demand-aware algorithm based on multiobjective optimization to jointly design the carrier allocation and precoding for better spectral efficiency and demand matching with proper management of the satellite resources. The optimization problem is non-convex, and we solve it using convex relaxation and successive convex approximation. Then, we evaluate the performance of the proposed algorithm through numerical results. It is shown that the proposed method outperforms the benchmark schemes in terms of resource utilization and demand satisfaction. [less ▲]

Cooperative Hybrid Networks with Active Relays and RISs for B5G: Applications, Challenges, and Research Directions

in IEEE Wireless Communications (2022)

Double-Phase-Shifter Based Hybrid Beamforming for mmWave DFRC in the Presence of Extended Target and Clutters

in IEEE Transactions on Wireless Communications ( Early Access ) (2022)

In millimeter-wave (mmWave) dual-function radar-communication (DFRC) systems, hybrid beamforming (HBF) is recognized as a promising technique utilizing a limited number of radio frequency chains. In this ... [more ▼]

In millimeter-wave (mmWave) dual-function radar-communication (DFRC) systems, hybrid beamforming (HBF) is recognized as a promising technique utilizing a limited number of radio frequency chains. In this work, in the presence of extended target and clutters, a HBF design based on the subarray connection architecture is proposed for a multiple-input multiple-output (MIMO) DFRC system. In this HBF, the double-phase-shifter (DPS) structure is embedded to further increase the design flexibility. We derive the communication spectral efficiency (SE) and radar signal-to-interference-plus-noise-ratio (SINR) with respect to the transmit HBF and radar receiver, and formulate the HBF design problem as the SE maximization subjecting to the radar SINR and power constraints. To solve the formulated nonconvex problem, the joinT Hybrid bEamforming and Radar rEceiver OptimizatioN (THEREON) is proposed, in which the radar receiver is optimized via the generalized eigenvalue decomposition, and the transmit HBF is updated with low complexity in a parallel manner using the consensus alternating direction method of multipliers (consensus-ADMM). Furthermore, we extend the proposed method to the multi-user multiple-input single-output (MU-MISO) scenario. Numerical simulations demonstrate the efficacy of the proposed algorithm and show that the solution provides a good trade-off between number of phase shifters and performance gain of the DPS HBF. [less ▲]

Energy Efficient Sparse Precoding Design for Satellite Communication System

Scientific Conference (2022)

Through precoding, the spectral efficiency of the system can be improved; thus, more users can benefit from 5G and beyond broadband services. However, complete precoding (using all precoding coefficients ... [more ▼]

Through precoding, the spectral efficiency of the system can be improved; thus, more users can benefit from 5G and beyond broadband services. However, complete precoding (using all precoding coefficients) may not be possible in practice due to the high signal processing complexity involved in calculating a large number of precoding coefficients and combining them with symbols for transmission. In this paper, we propose an energy-efficient sparse precoding design, where only a few precoding coefficients are used with lower power consumption depending on the demand. In this context, we formulate an optimization problem that minimizes the number of in-use precoding coefficients and the system power consumption while matching the per beam demand. This problem is nonconvex. Hence, we apply Lagrangian relaxation and successive convex approximation to convexify it. The proposed solution outperforms the benchmark scheme in power consumption and demand satisfaction with the additional advantage of sparse precoding design. [less ▲]

User Scheduling and Power Allocation for Precoded Multi-Beam High Throughput Satellite Systems With Individual Quality of Service Constraints

in IEEE Transactions on Vehicular Technology (Early Access) (2022)

For extensive coverage areas, multi-beam high throughput satellite (HTS) communication is a promising technology that plays a crucial role in delivering broadband services to many users with diverse ... [more ▼]

For extensive coverage areas, multi-beam high throughput satellite (HTS) communication is a promising technology that plays a crucial role in delivering broadband services to many users with diverse Quality of Service (QoS) requirements. This paper focuses on multi-beam HTS systems where all beams reuse the same spectrum. In particular, we propose a novel user scheduling and power allocation design capable of providing guarantees in terms of the individual QoS requirements while maximizing the system throughput under a limited power budget. Precoding is employed in the forward link to mitigate mutual interference among the users in multiple-access scenarios over different coherence time intervals. The combinatorial optimization structure from user scheduling requires an extremely high cost to obtain the global optimum even when a reduced number of users fit into a time slot. Therefore, we propose a heuristic algorithm yielding a good trade-off between performance and computational complexity, applicable to a static operation framework of geostationary (GEO) satellite networks. Although the power allocation optimization is signomial programming, non-convex on a standard form, the solution can be lower bounded by the global optimum of a geometric program with a hidden convex structure. A local solution to the joint user scheduling and power allocation problem is consequently obtained by a successive optimization approach. Numerical results demonstrate the effectiveness of our algorithms on GEO satellite networks by providing better QoS satisfaction combined with outstanding overall system throughput. [less ▲]

Joint Multislot Scheduling and Precoding for Unicast and Multicast Scenarios in Multiuser MISO Systems

in IEEE Transactions on Wireless Communications (2022), 21(7), 5004-5018

This paper studies the joint multislot design of user scheduling and precoding to minimize the time needed to serve all the users for unicast and multicast transmission in single-cell multiuser MISO ... [more ▼]

This paper studies the joint multislot design of user scheduling and precoding to minimize the time needed to serve all the users for unicast and multicast transmission in single-cell multiuser MISO downlink systems. In the literature, the joint design of scheduling and precoding is typically undertaken based on feedback from previous slots. In a system with time-varying channels and QoS requirements, joint multislot designs can achieve better performance since they have the flexibility to schedule users over multiple slots and also can split users across slots efficiently. Further, a joint multislot design can provide a feasible solution even when the sequential design fails. In this paper, scheduling is represented by a binary matrix where the rows represent users, columns represent slots and entries represent scheduling of users in the slots. Noticing that the users may not be permuted across slots for time-varying channels, service time needed for scheduling is rendered as the highest column index corresponding to non-zero columns. With the help of binary scheduling matrix, service time minimization is formulated as a structured mixed-Boolean fractional programming. Further, by exploiting the hidden convex-concave structure in the problem, a convex-concave procedure-based iterative algorithm is proposed. Finally, we vindicate the necessity and illustrate the superiority in performance of joint multislot design over the sequential solution through Monte-Carlo simulations. [less ▲]

Joint Beam Hopping and Carrier Aggregation in High Throughput Multi-Beam Satellite Systems

in IEEE Access (2022)

Beam hopping (BH) and carrier aggregation (CA) are two promising technologies for the next generation satellite communication systems to achieve several orders of magnitude increase in system capacity and ... [more ▼]

Beam hopping (BH) and carrier aggregation (CA) are two promising technologies for the next generation satellite communication systems to achieve several orders of magnitude increase in system capacity and to significantly improve the spectral efficiency. While BH allows a great flexibility in adapting the offered capacity to the heterogeneous demand, CA further enhances the user quality-of-service (QoS) by allowing it to pool resources from multiple adjacent beams. In this paper, we consider a multi-beam high throughput satellite (HTS) system that employs BH in conjunction with CA to capitalize on the mutual interplay between both techniques. Particularly, an innovative joint BH-CA scheme is proposed and analyzed in this work to utilize their individual competencies. This includes designing an efficient joint time-space beam illumination pattern for BH and multi-user aggregation strategy for CA. Through this, user-carrier assignment, transponder filling-rates, beams hopping pattern, and illumination duration are all simultaneously optimized by formulating a joint optimization problem as a multi-objective mixed integer linear programming problem (MINLP). Simulation results are provided to corroborate our analysis, demonstrate the design tradeoffs, and point out the potentials of the proposed joint BH-CA concept. Advantages of our BH-CA scheme versus the conventional BH method without employing CA are investigated and presented under the same system circumstances. [less ▲]

Satellite- and Cache-Assisted UAV: A Joint Cache Placement, Resource Allocation, and Trajectory Optimization for 6G Aerial Networks

in IEEE Open Journal of Vehicular Technology (2022), 3

This paper considers Low Earth Orbit (LEO) satellite- and cache-assisted unmanned aerial vehicle (UAV) communications for content delivery in terrestrial networks, which shows great potential for next ... [more ▼]

This paper considers Low Earth Orbit (LEO) satellite- and cache-assisted unmanned aerial vehicle (UAV) communications for content delivery in terrestrial networks, which shows great potential for next-generation systems to provide ubiquitous connectivity and high capacity. Specifically, caching is provided by the UAV to reduce backhaul congestion, and the LEO satellite supports the UAV’s backhaul link. In this context, we aim to maximize the minimum achievable throughput per ground user (GU) by jointly optimizing cache placement, the UAV’s resource allocation, and trajectory while cache capacity and flight time are limited. The formulated problem is challenging to solve directly due to its non-convexity and combinatorial nature. To find a solution, the problem is decomposed into three sub-problems: (1) cache placement optimization with fixed UAV resources and trajectory, followed by (2) the UAV resources optimization with fixed cache placement vector and trajectory, and finally, (3) we optimize the UAV trajectory with fixed cache placement and UAV resources. Based on the solutions of sub-problems, an efficient alternating algorithm is proposed utilizing the block coordinate descent (BCD) and successive convex approximation (SCA) methods. Simulation results show that the max-min throughput and total achievable throughput enhancement can be achieved by applying our proposed algorithm instead of other benchmark schemes. [less ▲]

Joint Parameter Estimation From Binary Observations Over Decentralized Channels

in IEEE Transactions on Signal Processing (2022), 70

In wireless sensor networks, due to the bandwidth constraint, the distributed nodes (DNs) might only provide binary representatives of the source signal, and then transmit them to the central node (CN ... [more ▼]

In wireless sensor networks, due to the bandwidth constraint, the distributed nodes (DNs) might only provide binary representatives of the source signal, and then transmit them to the central node (CN). In this paper, we consider the joint estimation of signal amplitude and background noise variance from binary observations over decentralized channels. We first analyze the Cramér–Rao lower bounds (CRLBs) of the parameters of interest and develop a quasilinear estimator (QLE), in which the desirable estimates can be obtained from several intermediate parameters linearly. Next, we consider a more realistic situation where the decentralized channel is noisy during the data transmission. Based on the error propagation model, the asymptotic analysis shows that the performance of the proposed QLE is mainly dominated by the thresholds of the quantizers, which encourages us to adopt a correlated quantization (CQ) scheme by exploiting the spatial correlation among background noises/channel noises. To ease the implementation of QLE in practice, an adaptive quantization (AQ) scheme is also proposed so as to obtain reasonable selections of the required thresholds. Finally, numerical simulations are provided to validate our theoretical findings. [less ▲]

Dual-DNN Assisted Optimization for Efficient Resource Scheduling in NOMA-Enabled Satellite Systems

Scientific Conference (2021, December 08)

In this paper, we apply non-orthogonal multiple access (NOMA) in satellite systems to assist data transmission for services with latency constraints. We investigate a problem to minimize the transmission ... [more ▼]

In this paper, we apply non-orthogonal multiple access (NOMA) in satellite systems to assist data transmission for services with latency constraints. We investigate a problem to minimize the transmission time by jointly optimizing power allocation and terminal-timeslot assignment for accomplishing a transmission task in NOMA-enabled satellite systems. The problem appears non-linear/non-convex with integer variables and can be equivalently reformulated in the format of mixed-integer convex programming (MICP). Conventional iterative methods may apply but at the expenses of high computational complexity in approaching the optimum or near-optimum. We propose a combined learning and optimization scheme to tackle the problem, where the primal MICP is decomposed into two learning-suited classification tasks and a power allocation problem. In the proposed scheme, the first learning task is to predict the integer variables while the second task is to guarantee the feasibility of the solutions. Numerical results show that the proposed algorithm outperforms benchmarks in terms of average computational time, transmission time performance, and feasibility guarantee. [less ▲]