Wireless power transfer (WPT) prolongs the lifetime of wireless sensor network by providing sustainable power supply to the distributed sensor nodes (SNs) via electromagnetic waves. To improve the energy transfer efficiency in a large WPT system, this paper proposes an adaptively directional WPT (AD-WPT) scheme, where the power beacons (PBs) adapt the energy beamforming strategy to SNs' locations by concentrating the transmit power on the nearby SNs within the efficient charging radius. With the aid of stochastic geometry, we derive the closed-form expressions of the distribution metrics of the aggregate received power at a typical SN. We analyze the optimal charging radius that maximizes the average received power. It is shown that both the optimal charging radius and maximized average received power decrease with the increased density of the SNs and the energy beamwidth. Finally, we show that the optimal AD-WPT can significantly improve the energy transfer efficiency compared to the traditional omnidirectional WPT.
The integration of intelligent reflecting surface (IRS) to multiple access networks is a cost-effective solution for boosting spectrum/energy efficiency and enlarging network coverage/connections. However, due to the new capability of IRS in reconfiguring the wireless propagation channels, it is fundamentally unknown which multiple access scheme is superior in the IRS-assisted wireless network. In this letter, we pursue a theoretical performance comparison between non-orthogonal multiple access (NOMA) and orthogonal multiple access (OMA) in the IRS-assisted downlink communication, for which the transmit power minimization problems are formulated under the discrete unit-modulus reflection constraint on each IRS element. We analyze the minimum transmit powers required by different multiple access schemes and compare them numerically, which turn out to not fully comply with the stereotyped superiority of NOMA over OMA in conventional systems without IRS. Moreover, to avoid the exponential complexity of the brute-force search for the optimal discrete IRS phase shifts, we propose a low-complexity solution to achieve near-optimal performance.
This paper studies low-complexity power control schemes to approach the capacity limits of multiple-input multiple-output orthogonal-frequency-division-multiplexing (MIMO-OFDM) channels under the assumption that perfect channel state information (CSI) is available at both the transmitter and the receiver. Two notions of channel capacity limit are considered, namely, the ergodic capacity for variable-rate transmission of no-delay-constrained (NDC) traffic and the delay-limited capacity for constant-rate transmission of delay-constrained (DC) traffic. Let M be the minimum between the number of transmit and receive antennas and N the number of subcarriers, we propose a subchannel grouping (SCG) technique, which divides the total number of MN space-frequency MIMO-OFDM subchannels into M grouped channels, each exhibiting a different fading statistics. A class of multitarget power control schemes are then proposed to allocate transmit power and rate to each grouped channel via different statistical water-filling (SWF) solutions. More specifically, multitarget constant-power (MT-CP) is proposed for transmission of NDC traffic and multitarget overall channel inversion (MT-OCI) for transmission of DC traffic. Furthermore, we consider the problem of transmission with mixed DC and NDC traffic and present for this case a low-complexity power control scheme which is based on hybrid MT-CP and MT-OCI. Because of SCG and SWF, the proposed schemes reduce significantly the computational complexity required by optimal power and rate allocation in MIMO-OFDM channels. Numerical examples are provided to evaluate the achievable rates of the proposed power control schemes and compare them with the capacity limits of MIMO-OFDM channels
Intelligent reflecting surface (IRS) is an emerging technology to enhance the spectral and energy efficiency of wireless communications cost-effectively. This letter considers a new multi-IRS aided wireless network where a cascaded line-of-sight (LoS) link is established between the base station (BS) and a remote user by leveraging the multi-hop signal reflection of selected IRSs. As compared to the conventional single-/double-hop IRS system, multi-hop IRS system provides more pronounced path diversity and cooperative passive beamforming gains, especially in the environment with dense obstacles. However, a more challenging joint active/passive beamforming and multi-hop beam routing problem also arises for maximizing the end-to-end channel gain. Furthermore, the number of IRS-associated channel coefficients increases drastically with the number of IRS hops. To tackle the above issues, in this letter we propose a new and efficient beam training based solution by considering the use of practical codebook-based BS/IRS active/passive beamforming without the need of explicit channel estimation. Instead of exhaustively or sequentially searching over all combinations of active and passive beam patterns for each beam route, a distributed beam training scheme is proposed to reduce the complexity, by exploiting the (nearly) time-invariant BS-IRS and inter-IRS channels and the cooperative training among the BS and IRSs' controllers. Simulation results show that our proposed design achieves the end-to-end channel gain close to that of the sequential beam search, but at a much lower training overhead and complexity.
This paper considers spectrum sharing between a cognitive radio (CR) and a primary radio (PR) where the CR protects the PR transmission by regulating the resultant interference power level at the PR receiver to be below some predefined threshold. The interference-power constraint at the PR receiver is usually one of the following two types: average interference power (AIP) constraint that regulates the average power level over different fading states and peak interference power (PIP) constraint that limits the peak power level at each fading state. From CR's perspective, AIP constraint is more favorable than PIP constraint because of its more flexibility for dynamic power allocations. On the contrary, from the perspective of protecting the PR, the more restrictive PIP constraint appears at a first glance to be a better option. Some surprisingly, this paper shows that in terms of various forms of capacity limits achievable for the PR fading channel, namely, ergodic and outage capacities, AIP constraint is also superior over PIP constraint. This result is based upon an interesting interference diversity phenomenon, i.e., variable interference power levels at the PR receiver in the AIP case are more advantageous over constant ones in the PIP case for minimizing the resulted PR capacity losses. Therefore, AIP constraint leads to larger fading channel capacities over PIP constraint for both CR and PR transmissions.
Intelligent reflecting surfaces (IRSs), active and/or passive, can be densely deployed in complex environments to significantly enhance wireless network coverage for both wireless information transfer (WIT) and wireless power transfer (WPT). In this letter, we study the downlink WIT/WPT from a multi-antenna base station to a single-antenna user over a multi-active/passive IRS (AIRS/PIRS)-enabled wireless link. In particular, we derive the location of the AIRS with those of the other PIRSs being fixed to maximize the received signal-to-noise ratio (SNR) and signal power at the user in the cases of WIT and WPT, respectively. The derived solutions reveal that the optimal AIRS deployment is generally different for WIT versus WPT due to the different roles of AIRS-induced amplification noise. Furthermore, both analytical and numerical results are provided to show the conditions under which the proposed AIRS deployment strategy yields superior performance to other baseline deployment strategies as well as the conventional all-PIRS enabled WIT/WPT.
Unmanned aerial vehicle (UAV) can be used as an aerial base station to provide rapid wireless connectivity to ground users. Given UAV's agility and mobility, a key problem is how to adapt UAV deployment to best cater to the instantaneous wireless traffic in a territory. In this paper, we propose a traffic-aware adaptive UAV deployment scheme in a UAV-aided communication network, where the UAV initiated at the cell center adapts its displacement direction and distance to the spatial randomness of the Poisson distributed mobile users within its target cell. In each realization, the UAV chooses its displacement direction based on a simple majority rule, i.e., to fly to the sector that has the greatest number of users. To balance the service for the users in different sectors, we further optimize the UAV's displacement distance in the chosen sector to maximize the average throughput. We show that the optimal displacement distance under the proposed scheme decreases with the user density. Extensive simulations illustrate that the proposed adaptive deployment scheme outperforms the traditional non-adaptive scheme, where the performance gain is especially significant for small user density.
Unmanned aerial vehicle (UAV) as an aerial base station is a promising technology to rapidly provide wireless connectivity to ground users. Given UAV's agility and mobility, a key question is how to adapt UAV deployment to the best cater to instantaneous wireless traffic in a territory. In this paper, we propose an adaptive deployment scheme for a UAV-aided communication network, where the UAV adapts its displacement direction and distance to serve randomly moving users' instantaneous traffic in the target cell. In our adaptive scheme, the UAV does not need to learn users' exact locations in real time, but chooses its displacement direction based on a simple majority rule by flying to the spatial sector with the greatest number of users in the cell. To balance the service qualities of the users in different sectors, we further optimize the UAV's displacement distance in the chosen sector to maximize the average throughput and the successful transmission probability, respectively. We prove that the optimal displacement distance for average throughput maximization decreases with the user density: the UAV moves to the center of the chosen sector when the user density is small and the UAV displacement becomes mild when the user density is large. In contrast, the optimal displacement distance for success probability maximization does not necessarily decrease with the user density and further depends on the target signal-to-noise ratio (SNR) threshold. The extensive simulations show that the proposed adaptive deployment scheme outperforms the traditional non-adaptive scheme, especially when the user density is not large.
No abstract is provided for this article.
In southwest China, red mudstone fill material (RMF) is widely used in constructing railway subgrades to substitute the conventional unbound granular materials (UGMs). Besides the strain-level dependent dynamic properties, RMF significantly depends on loading cycles. However, such an effect has yet to be incorporated into the current design method, which would lead to a considerable misprediction in dynamic responses of the RMF subgrade during the operation period. This paper presents a comprehensive study of long-term dynamic properties of RMF (a silty clay) over a range of water contents and cyclic stresses. The objective is to establish a normalization framework of dynamic properties that considers the effect of large numbers of cyclic loading. With this emphasis, 40 cyclic triaxial tests with 50000 loading cycles were conducted on RMF specimens compacted at various water contents. Two-stage behavior has been identified in equivalent Young’s modulus and damping ratio evolutions. An exponential model is thus proposed to capture the two-stage pattern. The proposed normalization procedure showed a competent availability for the characterization of equivalent Young’s modulus and damping ratio at different loading cycles. Soil fabric also played a decisive role in evaluating RMF’s dynamic responses. Evidence of microfabric effect on the dynamic responses of RMF was strengthened by the Mercury intrusion porosimetry (MIP) and scanning electron microscope (SEM) analysis.
In current interframe video compression systems, the encoder performs predictive coding to exploit the similarities of successive frames. The Wyner-Ziv theorem on source coding with side information available only at the decoder suggests that an asymmetric video codec, where individual frames are encoded separately, but decoded conditionally (given temporally adjacent frames) could achieve similar efficiency. We report the first results on a Wyner-Ziv coding scheme for motion video that uses intraframe encoding, but interframe decoding.
Automatic synchronous parallel operation is one of main functions of marine power station automation.Taking a semi-submersible vessel as the research object, this paper mainly describes the conditions of synchronous parallel operation, detection and achievement way of synchronous parallel operation.According to the requirement, the marine power station simulation is designed based on the Visual C++ platform.Through experimental validation, the testing results show that the marine power station simulation has a high reliability and good anti -interference.
