25 research outputs found
Towards 6G-Enabled Internet of Things with IRS-Empowered Backscatter-Assisted WPCNs
Wireless powered communication networks (WPCNs) are expected to play a key role in the forthcoming 6G systems. However, they have not yet found their way to large-scale practical implementations due to their inherent shortcomings such as the low efficiency of energy transfer and information transmission. In this thesis, we aim to study the integration of WPCNs with other novel technologies of backscatter communication and intelligent reflecting surface (IRS) to enhance the performance and improve the efficiency of these networks so as to prepare them for being seamlessly fitted into the 6G ecosystem. We first study the incorporation of backscatter communication into conventional WPCNs and investigate the performance of backscatter-assisted WPCNs (BS-WPCNs). We then study the inclusion of IRS into the WPCN environment, where an IRS is used for improving the performance of energy transfer and information transmission in WPCNs. After that, the simultaneous integration of backscatter communication and IRS technologies into WPCNs is investigated, where the analyses show the significant performance gains that can be achieved by this integration
Sum Throughput Maximization in Multi-Tag Backscattering to Multiantenna Reader
Backscatter communication (BSC) is being realized as the core technology for
pervasive sustainable Internet-of-Things applications. However, owing to the
resource-limitations of passive tags, the efficient usage of multiple antennas
at the reader is essential for both downlink excitation and uplink detection.
This work targets at maximizing the achievable sum-backscattered-throughput by
jointly optimizing the transceiver (TRX) design at the reader and
backscattering coefficients (BC) at the tags. Since, this joint problem is
nonconvex, we first present individually-optimal designs for the TRX and BC. We
show that with precoder and {combiner} designs at the reader respectively
targeting downlink energy beamforming and uplink Wiener filtering operations,
the BC optimization at tags can be reduced to a binary power control problem.
Next, the asymptotically-optimal joint-TRX-BC designs are proposed for both low
and high signal-to-noise-ratio regimes. Based on these developments, an
iterative low-complexity algorithm is proposed to yield an efficient
jointly-suboptimal design. Thereafter, we discuss the practical utility of the
proposed designs to other application settings like wireless powered
communication networks and BSC with imperfect channel state information.
Lastly, selected numerical results, validating the analysis and shedding novel
insights, demonstrate that the proposed designs can yield significant
enhancement in the sum-backscattered throughput over existing benchmarks.Comment: 17 pages, 5 figures, accepted for publication in IEEE Transactions on
Communication
A Comprehensive Overview on 5G-and-Beyond Networks with UAVs: From Communications to Sensing and Intelligence
Due to the advancements in cellular technologies and the dense deployment of
cellular infrastructure, integrating unmanned aerial vehicles (UAVs) into the
fifth-generation (5G) and beyond cellular networks is a promising solution to
achieve safe UAV operation as well as enabling diversified applications with
mission-specific payload data delivery. In particular, 5G networks need to
support three typical usage scenarios, namely, enhanced mobile broadband
(eMBB), ultra-reliable low-latency communications (URLLC), and massive
machine-type communications (mMTC). On the one hand, UAVs can be leveraged as
cost-effective aerial platforms to provide ground users with enhanced
communication services by exploiting their high cruising altitude and
controllable maneuverability in three-dimensional (3D) space. On the other
hand, providing such communication services simultaneously for both UAV and
ground users poses new challenges due to the need for ubiquitous 3D signal
coverage as well as the strong air-ground network interference. Besides the
requirement of high-performance wireless communications, the ability to support
effective and efficient sensing as well as network intelligence is also
essential for 5G-and-beyond 3D heterogeneous wireless networks with coexisting
aerial and ground users. In this paper, we provide a comprehensive overview of
the latest research efforts on integrating UAVs into cellular networks, with an
emphasis on how to exploit advanced techniques (e.g., intelligent reflecting
surface, short packet transmission, energy harvesting, joint communication and
radar sensing, and edge intelligence) to meet the diversified service
requirements of next-generation wireless systems. Moreover, we highlight
important directions for further investigation in future work.Comment: Accepted by IEEE JSA
Energy Optimization of Smart Water Systems using UAV Enabled Zero-Power Wireless Communication Networks
Real-time energy consumption is a crucial consideration when assessing the effectiveness and efficiency of communication using energy hungry devices. Utilizing new technologies such as UAV-enabled wireless powered communication networks (WPCN) and 3D beamforming, and then a combination of static and dynamic optimization methodologies are combined to improve energy usage in water distribution systems (WDS).
A proposed static optimization technique termed the Dome packing method and dynamic optimization methods such as extremum seeking are employed to generate optimum placement and trajectories of the UAV with respect to the ground nodes (GN) in a WDS.
In this thesis, a wireless communication network powered by a UAV serves as a hybrid access point to manage many GNsin WDS. The GNs are water quality sensors that collect radio frequency (RF) energy from the RF signals delivered by the UAV and utilise this energy to relay information via an uplink. Optimum strategies are demonstrated to efficiently handle this process as part of a zero-power system: removing the need for manual battery charging of devices, while at the same time optimizing energy and data transfer over WPCN.
Since static optimization does not account for the UAV's dynamics, dynamic optimization techniques are also necessary. By developing an efficient trajectory, the suggested technique also reduces the overall flying duration and, therefore, the UAV's energy consumption. This combination of techniques also drastically reduces the complexity and calculation overhead of purely high order static optimizations.
To test and validate the efficacy of the extremum seeking implementation, comparison with the optimal sliding mode technique is also undertaken. These approaches are applied to ten distinct case studies by randomly relocating the GNs to various positions. The findings from a random sample of four of these is presented, which reveal that the proposed strategy reduces the UAV's energy usage significantly by about 16 percent compared to existing methods.
The (hybrid) static and dynamic zero-power optimization strategies demonstrated here are readily extendable to the control of water quality and pollution in natural freshwater resources and this will be discussed at the end of this thesis
Next-Generation Full Duplex Networking System Empowered by Reconfigurable Intelligent Surfaces
Full duplex (FD) radio has attracted extensive attention due to its co-time
and co-frequency transceiving capability. {However, the potential gain brought
by FD radios is closely related to the management of self-interference (SI),
which imposes high or even stringent requirements on SI cancellation (SIC)
techniques. When the FD deployment evolves into next-generation mobile
networking, the SI problem becomes more complicated, significantly limiting its
potential gains.} In this paper, we conceive a multi-cell FD networking scheme
by deploying a reconfigurable intelligent surface (RIS) at the cell boundary to
configure the radio environment proactively. To achieve the full potential of
the system, we aim to maximize the sum rate (SR) of multiple cells by jointly
optimizing the transmit precoding (TPC) matrices at FD base stations (BSs) and
users and the phase shift matrix at RIS. Since the original problem is
non-convex, we reformulate and decouple it into a pair of subproblems by
utilizing the relationship between the SR and minimum mean square error (MMSE).
The optimal solutions of TPC matrices are obtained in closed form, while both
complex circle manifold (CCM) and successive convex approximation (SCA) based
algorithms are developed to resolve the phase shift matrix suboptimally. Our
simulation results show that introducing an RIS into an FD networking system
not only improves the overall SR significantly but also enhances the cell edge
performance prominently. More importantly, we validate that the RIS deployment
with optimized phase shifts can reduce the requirement for SIC and the number
of BS antennas, which further reduces the hardware cost and power consumption,
especially with a sufficient number of reflecting elements. As a result, the
utilization of an RIS enables the originally cumbersome FD networking system to
become efficient and practical.Comment: 15 pages, 14 figure
Wireless-powered cooperative communications: protocol design, performance analysis and resource allocation
Radio frequency (RF) energy transfer technique has attracted much attention and has recently been regarded as a key enabling technique for wireless-powered communications. However, the high attenuation of RF energy transfer over distance has greatly limited the performance and applications of WPCNs in practical scenarios. To overcome this essential hurdle, in this thesis we propose to combat the propagation attenuation by incorporating cooperative communication techniques in WPCNs. This opens a new paradigm named wireless-powered cooperative communication and raises many new research opportunities with promising applications. In this thesis, we focus on the novel protocol design, performance analysis and resource allocation of wireless-powered cooperative communication networks (WPCCNs). We first propose a harvest-then-cooperate (HTC) protocol for WPCCNs, where the wireless-powered source and relay(s) harvest energy from the AP in the downlink (DL) and work cooperatively in the uplink (UL) for transmitting source information. The average throughput performance of the HTC protocol with two single relay selection schemes is analyzed. We then design two novel protocols and study the optimal resource allocation for another setup of WPCCNs with a hybrid relay that has a constant power supply. Besides cooperating with the source for UL information transmission, the hybrid relay also transmits RF energy concurrently with the AP during the DL energy transfer phase. Subsequently, we adopt the Stackelberg game to model the strategic interactions in power beacon (PB)-assisted WPCCNs, where PBs are deployed to provide wireless charging services to wireless-powered users via RF energy transfer and are installed by different operators with the AP. Finally, we develop a distributed power splitting framework using non-cooperative game theory for a large-scale WPCCN, where multiple source-destination pairs communicate through their dedicated wireless-powered relays