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

in IEEE Transactions on Wireless Communications (2022)

Dual-Function Radar-Communication Systems with Constant-Modulus and Similarity Constraints

in IEEE 12th Sensor Array and Multichannel Signal Processing Workshop (SAM) (2022)

In this paper, the problem of joint transmit waveform and receive filter design for dual-function radar-communication (DFRC) systems is studied. A multiple antenna base station (BS) serving multiple ... [more ▼]

In this paper, the problem of joint transmit waveform and receive filter design for dual-function radar-communication (DFRC) systems is studied. A multiple antenna base station (BS) serving multiple single antenna users on the downlink is assumed. Furthermore, the BS simultaneously accommodates sensing capabilities in the form of point-like target detection from the reflected return signals in a signal-dependent interference environment. The core objective of the present paper is to design the optimal waveform and radar receive filter such that the derived waveform satisfies constant-modulus and similarity to known waveform constraints that are of particular importance to the radar's part operation. The proposed designs are derived through the solution to difficult non-convex optimization problems. To that end, novel algorithmic solutions with guaranteed convergence are developed for the solution of the aforementioned problems. The effectiveness of the proposed solutions is verified via simulations. [less ▲]

Reconfigurable Intelligent Surface-Assisted Cell-Free Massive MIMO Systems Over Spatially-Correlated Channels

in IEEE Transactions on Wireless Communications (2022), 21(7), 5106-5128

Cell-Free Massive multiple-input multiple-output (MIMO) and reconfigurable intelligent surface (RIS) are two promising technologies for application to beyond-5G networks. This paper considers Cell-Free ... [more ▼]

Cell-Free Massive multiple-input multiple-output (MIMO) and reconfigurable intelligent surface (RIS) are two promising technologies for application to beyond-5G networks. This paper considers Cell-Free Massive MIMO systems with the assistance of an RIS for enhancing the system performance under the presence of spatial correlation among the engineered scattering elements of the RIS. Distributed maximum-ratio processing is considered at the access points (APs). We introduce an aggregated channel estimation approach that provides sufficient information for data processing with the main benefit of reducing the overhead required for channel estimation. The considered system is studied by using asymptotic analysis which lets the number of APs and/or the number of RIS elements grow large. A lower bound for the channel capacity is obtained for a finite number of APs and engineered scattering elements of the RIS, and closed-form expressions for the uplink and downlink ergodic net throughput are formulated in terms of only the channel statistics. Based on the obtained analytical frameworks, we unveil the impact of channel correlation, the number of RIS elements, and the pilot contamination on the net throughput of each user. In addition, a simple control scheme for optimizing the configuration of the engineered scattering elements of the RIS is proposed, which is shown to increase the channel estimation quality, and, hence, the system performance. Numerical results demonstrate the effectiveness of the proposed system design and performance analysis. In particular, the performance benefits of using RISs in Cell-Free Massive MIMO systems are confirmed, especially if the direct links between the APs and the users are of insufficient quality with high probability. [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 ▲]

Symbiotic Radio based Spectrum Sharing in Cooperative UAV-IRS Wireless Networks

in Proceedings of IEEE VTC2022-Spring (2022)

Ambient backscatter communication (AmBC) technology can potentially offer spectral- and energy-efficient solutions for future wireless systems. This paper proposes a novel design to facilitate the ... [more ▼]

Ambient backscatter communication (AmBC) technology can potentially offer spectral- and energy-efficient solutions for future wireless systems. This paper proposes a novel design to facilitate the spectrum sharing between a secondary system and a primary system based on the AmBC technique in intelligent reflective surface (IRS)-assisted unmanned aerial vehicle (UAV) networks. In particular, an IRS-aided UAV cooperatively relays the transmission from a terrestrial primary source node to a user equipment on the ground. On the other hand, leveraging on the AmBC technology, a terrestrial secondary node transmits its information to a terrestrial secondary receiver by modulating and backscattering the ambient relayed radio frequency (RF) signals from the UAV-IRS. The performance of such a system setup is analyzed by deriving the expressions of outage probability and ergodic spectral efficiency. Finally, we present the numerical results to provide useful insights into the system design and also validate the derived theoretical results using Monte Carlo simulations. [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 ▲]

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 ▲]

Learning-Based Multiplexing of Grant-Based and Grant-Free Heterogeneous Services with Short Packets

in Proceedings of 2021 IEEE Global Communications Conference (GLOBECOM) (2021, December)

In this paper, we investigate the multiplexing of grant-based (GB) and grant-free (GF) device transmissions in an uplink heterogeneous network (HetNet), namely GB-GF HetNet, where the devices transmit ... [more ▼]

In this paper, we investigate the multiplexing of grant-based (GB) and grant-free (GF) device transmissions in an uplink heterogeneous network (HetNet), namely GB-GF HetNet, where the devices transmit their information using low-rate short data packets. Specifically, GB devices are granted unique time-slots for their transmissions. In contrast, GF devices can randomly select time-slots to transmit their messages utilizing the GF non-orthogonal multiple access (NOMA), which has emerged as a promising enabler for massive access and reducing access latency. However, random access (RA) in the GF NOMA can cause collisions and severe interference, leading to system performance degradation. To overcome this issue, we propose a multiple access (MA) protocol based on reinforcement learning for effective RA slots allocation. The proposed learning method aims to guarantee that the GF devices do not cause any collisions to the GB devices and the number of GF devices choosing the same time-slot does not exceed a predetermined threshold to reduce the interference. In addition, based on the results of the RA slots allocation using the proposed method, we derive the approximate closed-form expressions of the average decoding error probability (ADEP) for all devices to characterize the system performance. Our results presented in terms of access efficiency (AE), collision probability (CP), and overall ADEP (OADEP), show that our proposed method can ensure a smooth operation of the GB and GF devices within the same network while significantly minimizing the collision and interference among the device transmissions in the GB-GF HetNet. [less ▲]

Learning-Assisted User Clustering in Cell-Free Massive MIMO-NOMA Networks

in IEEE Transactions on Vehicular Technology (2021), 70(12), 12872-12887

The superior spectral efficiency (SE) and user fairness feature of non-orthogonal multiple access (NOMA) systems are achieved by exploiting user clustering (UC) more efficiently. However, a random UC ... [more ▼]

The superior spectral efficiency (SE) and user fairness feature of non-orthogonal multiple access (NOMA) systems are achieved by exploiting user clustering (UC) more efficiently. However, a random UC certainly results in a suboptimal solution while an exhaustive search method comes at the cost of high complexity, especially for systems of medium-to-large size. To address this problem, we develop two efficient unsupervised machine learning based UC algorithms, namely k-means++ and improved k-means++, to effectively cluster users into disjoint clusters in cell-free massive multiple-input multiple-output (CFmMIMO) system. Adopting full-pilot zero-forcing at access points (APs) to comprehensively assess the system performance, we formulate the sum SE optimization problem taking into account power constraints at APs, necessary conditions for implementing successive interference cancellation, and required SE constraints at user equipments. The formulated optimization problem is highly non-convex, and thus, it is difficult to obtain the global optimal solution. Therefore, we develop a simple yet efficient iterative algorithm for its solution. In addition, the performance of collocated massive MIMO-NOMA (COmMIMO-NOMA) system is also characterized. Numerical results are provided to show the superior performance of the proposed UC algorithms compared to baseline schemes. The effectiveness of applying NOMA in CFmMIMO and COmMIMO systems is also validated. [less ▲]

Hybrid Beamforming for Terahertz Joint Ultra-Massive MIMO Radar-Communications

in IEEE Journal of Selected Topics in Signal Processing (2021), 15(6), 1468-1483

In this paper, we investigate the hybrid beamforming problem in joint radar-communications at terahertz (THz) bands. In order to address the extremely high attenuation at THz, ultra-massive multiple-input ... [more ▼]

In this paper, we investigate the hybrid beamforming problem in joint radar-communications at terahertz (THz) bands. In order to address the extremely high attenuation at THz, ultra-massive multiple-input multiple-output (UM-MIMO) antenna systems have been proposed for THz communications to compensate propagation losses. Further, we propose a new group-of-subarrays (GoSA) UM-MIMO structure to reduce the hardware cost. We formulate the GoSA beamformer design as an optimization problem to provide a trade-off between the unconstrained communications beamformers and the desired radar beamformers. Numerical experiments demonstrate that the proposed approach outperforms the conventional approaches in terms of spectral efficiency and hardware costs. [less ▲]