This paper studies a two-link interference channel (IFC) with simultaneous wireless information and power transfer (SWIPT). We aim to maximize the minimum signal to interference plus noise ratio (SINR) of the two links by jointly designing the power allocations at the transmitters and the power splitting (PS) ratios at the receivers under both the individual minimum energy harvesting (EH) constraints and maximum transmit power constraints. We first explore the properties of this non-convex problem and its optimal solution, and then design a centralized algorithm to find the optimal solution. We further propose a distributed algorithm for practical systems, where the transmit powers and PS ratios converge to the optimal solution through an iterative update process. Numerical results show that the proposed algorithms provide an improved trade-off in the achievable (max-min) SINR versus harvested energy as compared with other heuristic designs.
In a net-zero carbon power grid (NZCPG) with a relatively high proportion of renewable energy sources, significant power fluctuations occur, severely constraining the development of both the NZCPG and the New Urban Power Grid (NUPG). In the NZCPG, the proportion of traditional hydro and thermal power units used to mitigate power fluctuations has decreased. It is necessary to explore the load resources in the NUPG to stabilize the power fluctuation between the NUPG and the NZCPG, and to reduce the operating pressure of the NZCPG. Firstly, this paper proposes a method for developing external tie line schedules based on the load operation band (LOB) to relax the constraints on the schedule for the NZCPG. Secondly, A revised load response aggregation model is proposed to improve the aggregation accuracy under uncertainty factors by online correcting their impact on the load response characteristics. Thirdly, considering the flexible loads in NUPG can only compensate for a part of the power fluctuation, this paper proposes a method to judge the power fluctuation that these loads can offset. Two PFS optimal strategies are proposed among NUPG partitions considering deviation penalty and within each NUPG partition reducing the number of participated load-users. This paper focuses on the PFS in bulk NZCPGs other than in the distribution grids and microgrids. Our work can effectively smooth the power fluctuation within NUPG regulation capability meanwhile reducing the number of participated load-users. Fourthly, a method is proposed to judge the power fluctuation beyond NUPG regulation capacity in NUPG. Using the actual load response capacity, the over-amplitude/time layered smoothing strategy with optimal load is proposed, which can offset the power fluctuation of the bulk NZCPG to the largest extent. Finally, the IEEE-39 system is used to verify the effectiveness of the proposed methods. © 2017 Elsevier Inc. All rights reserved.
Multi-antenna precoding effectively mitigates the interference in wireless networks. However, the precoding efficiency can be significantly degraded by the overhead due to the required feedback of channel state information (CSI). This paper addresses such an issue by proposing a systematic method of designing precoders for the two-user multiple-input-multiple-output (MIMO) interference channels based on finite-rate CSI feedback from receivers to their interferers, called cooperative feedback. Specifically, each precoder is decomposed into inner and outer precoders for nulling interference and improving the data link array gain, respectively. The inner precoders are further designed to suppress residual interference resulting from finite-rate cooperative feedback. To regulate residual interference due to precoder quantization, additional scalar cooperative feedback signals are designed to control transmitters' power using different criteria including applying interference margins, maximizing sum throughput, and minimizing outage probability. Simulation shows that such additional feedback effectively alleviates performance degradation due to quantized precoder feedback.
Passenger train remote monitor system consists of monitoring centre,data transmission net and termination aboard the car,adopting GPRS and internet as media,data transmission between monitoring centre and termination is implemented.After the design scheme for the whole system is presented,the hardware and software design schemes of the termination are introduced mainly.The front machine of termination controls GPRS model communicating with monitoring centre by sending AT instructions via one serial port,and MCU monitors state of GPRS model via the other serial port of the model,once abnormal state appears,MCU resets the model,then keeps termination on-line all the time.The application shows that this system has good performance.
This paper proposes a novel digital predistortion technique to effectively linearize concurrent dual-band (DB) envelope tracking (ET) power amplifiers (PAs) with reduced bandwidth requirements for both RF and envelope paths. Based on a gallium-nitride (GaN) ET PA, the concurrent DB system was implemented by employing two 5 MHz OFDM signals at the center frequency of 2.0 GHz and 2.6 GHz with linearization bandwidth that is limited to only 15 MHz. The PA in-band and out-of-band performance was evaluated with an improvement of 26 dB and 21 dB for normalized mean square error (NMSE) and adjacent channel power ratio (ACPR), respectively.
This paper studies the optimal power allocation for outage probability minimization in point-to-point fading channels with the energy-harvesting constraints and channel distribution information (CDI) at the transmitter. Both the cases with non-causal and causal energy state information (ESI) are considered, which correspond to the energy-harvesting (EH) rates being known and unknown prior to the transmissions, respectively. For the non-causal ESI case, the average outage probability minimization problem over a finite horizon of N EH periods is shown to be non-convex for a large class of practical fading channels. However, the globally optimal "offline" power allocation is obtained by a forward search algorithm with at most N one-dimensional searches, and the optimal power profile is shown to be non-decreasing over time and have an interesting "save-then-transmit" structure. In particular, for the special case of N=1, our result revisits the classic outage capacity for fading channels with uniform power allocation. Moreover, for the case with causal ESI, we propose both the optimal and suboptimal "online" power allocation algorithms, by applying the technique of dynamic programming and exploring the structure of optimal offline solutions, respectively.
The line-of-sight (LoS) dominant air-ground channels have posed critical interference issues in cellular-connected unmanned aerial vehicle (UAV) communications. In this paper, we propose a new base station (BS) cooperative beamforming (CB) technique for the cellular downlink to mitigate the strong interference caused by the co-channel terrestrial transmissions to the UAV. Besides the conventional CB by cooperatively transmitting the UAV's message, the serving BSs of the UAV exploit a novel CB-based interference transmission scheme to effectively suppress the terrestrial interference to the UAV. Specifically, the co-channel terrestrial users' messages are shared with the UAV's serving BSs and transmitted via CB so as to cancel their resultant interference at the UAV's receiver. To optimally balance between the CB gains for UAV signal enhancement and terrestrial interference cancellation, we formulate a new problem to maximize the UAV's receive signal-to-interference-plus-noise ratio (SINR) by jointly optimizing the power allocations at all of its serving BSs for transmitting the UAV's and co-channel terrestrial users' messages. First, we derive the closed-form optimal solution to this problem in the special case of one serving BS for the UAV and draw useful insights. Then, we propose an algorithm to solve the problem optimally in the general case. As the optimal solution requires centralized implementation with exorbitant message/channel information exchanges among the BSs, we further propose a distributed algorithm that is amenable to practical implementation, based on a new divide-and-conquer approach, whereby each co-channel BS divides its perceived interference to the UAV into multiple portions, each to be canceled by a different serving BS of the UAV with its best effort. Numerical results show that the proposed centralized and distributed CB schemes with interference transmission and cancellation (ITC) can both significantly improve the UAV's downlink performance as compared to the conventional CB without applying ITC.
In this paper, we consider simultaneous wireless information and power transfer (SWIPT) in orthogonal frequency division multiple access (OFDMA) systems with the coexistence of information receivers (IRs) and energy receivers (ERs). The IRs are served with best-effort secrecy data and the ERs harvest energy with minimum required harvested power. To enhance physical-layer security and yet satisfy energy harvesting requirements, we introduce a new frequency-domain artificial noise based approach. We study the optimal resource allocation for the weighted sum secrecy rate maximization via transmit power and subcarrier allocation. The considered problem is non-convex, while we propose an efficient algorithm for solving it based on Lagrange duality method. Simulation results illustrate the effectiveness of the proposed algorithm as compared against other heuristic schemes.
Dispatching unmanned aerial vehicles (UAVs) to harvest sensing-data from distributed sensors is expected to significantly improve the data collection efficiency in conventional wireless sensor networks (WSNs). In this paper, we consider a UAV-enabled WSN, where a flying UAV is employed to collect data from multiple sensor nodes (SNs). Our objective is to maximize the minimum average data collection rate from all SNs subject to a prescribed reliability constraint for each SN by jointly optimizing the UAV communication scheduling and three-dimensional (3D) trajectory. Different from the existing works that assume the simplified line-of-sight (LoS) UAV-ground channels, we consider the more practically accurate angle-dependent Rician fading channels between the UAV and SNs with the Rician factors determined by the corresponding UAV-SN elevation angles. However, the formulated optimization problem is intractable due to the lack of a closed-form expression for a key parameter termed effective fading power that characterizes the achievable rate given the reliability requirement in terms of outage probability. To tackle this difficulty, we first approximate the parameter by a logistic (“S” shape) function with respect to the 3D UAV trajectory by using the data regression method. Then, the original problem is reformulated to an approximate form, which, however, is still challenging to solve due to its non-convexity. As such, we further propose an efficient algorithm to derive its suboptimal solution by using the block coordinate descent technique, which iteratively optimizes the communication scheduling, the UAV’s horizontal trajectory, and its vertical trajectory. The latter two subproblems are shown to be non-convex, while locally optimal solutions are obtained for them by using the successive convex approximation technique. Finally, extensive numerical results are provided to evaluate the performance of the proposed algorithm and draw new insights on the 3D UAV trajectory under the Rician fading as compared to conventional LoS channel models.
Intelligent reflecting surface (IRS) can be densely deployed in wireless networks to significantly enhance the communication channels. In this letter, we consider the downlink transmission from a multi-antenna base station (BS) to a single-antenna user, by exploiting the cooperative passive beamforming (CPB) and line-of-sight (LoS) path diversity gains of multi-IRS signal reflection. Unlike existing works where only one single multi-IRS reflection path from the BS to user is selected, we propose a new and more general <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">multi-path beam routing</i> scheme. Specifically, the BS sends the user’s information signal via multiple orthogonal active beams (termed as <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">active beam splitting</i> ), which point towards different IRSs. Then, these beamed signals are subsequently reflected by selected IRSs via their CPB in different paths, and finally coherently combined at the user’s receiver (thus named <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">passive beam combining</i> ). For this scheme, we formulate a new multi-path beam routing design problem to jointly optimize the number of IRS reflection paths, the selected IRSs for each of the reflection paths, the active/passive beamforming at the BS/each selected IRS, as well as the BS’s power allocation over different active beams, so as to maximize the received signal power at the user. To solve this challenging problem, we first derive the optimal BS/IRS beamforming and BS power allocation for a given set of reflection paths. The clique-based approach in graph theory is then applied to solve the remaining multi-path selection problem efficiently. Simulation results show that our proposed multi-path beam routing scheme significantly outperforms its conventional single-path beam routing special case.
This paper studies the cooperative interference control in a two-cell downlink OFDMA system, which can be modeled as an interfering broadcast channel. It is assumed that each cell can simultaneously access the same frequency band, which corresponds to a universal frequency-reuse in cellular systems. We study the joint power and subcarrier allocation over the two cells to maximize their sum throughput for both centralized and decentralized implementation. Specifically, the decentralized allocation is achieved via a new interactive interference control approach, where the two cells independently implement resource allocation to maximize individual throughput, subject to mutual interference power constraints. Simulation results show that the proposed decentralized resource allocation scheme achieves the system throughput close to that with the optimal centralized scheme, and also provides significant gains via cooperative interference control as compared to existing schemes.
