Power allocation for wireless powered MIMO transmissions with non-linear RF energy conversion models

This letter considers spectrum sharing between a multiuser multiple-input multiple-output (MIMO) wireless energy transfer (WET) system and a coexisting point-to-point MIMO wireless information transmission (WIT) system, where WET generates interference to WIT and degrades its throughput performance. We show that due to the interference, the WIT system suffers from a loss of the degrees of freedom (DoF) proportional to the number of energy beams sent by the energy transmitter (ET), which, in general, needs to be larger than one to optimize the multiuser WET with user fairness consideration. To minimize the DoF loss in WIT, we further propose a new single-beam energy transmission scheme based on the principle of time sharing, where the ET transmits one of the optimal energy beams at each time. This new scheme achieves the same optimal performance for the WET system, and minimizes the impact of its interference to the WIT system.

This paper considers a single-antenna wireless- powered communication network (WPCN) over a flat- fading channel. We show that, by using our probabilistic harvest-and-transmit (PHAT) strategy, which requires the knowledge of instantaneous full channel state information (CSI) and fading probability distribution, the ergodic throughput of this system may be greatly increased relative to that achieved by the harvest-then- transmit (HTT) protocol. To do so, instead of dividing every frame to the uplink (UL) and downlink (DL), the channel is allocated to the UL wireless information transmission (WIT) and DL wireless power transfer (WPT) based on the estimated channel power gain. In other words, based on the fading probability distribution, we will derive some thresholds that determine the association of a frame to the DL WPT or UL WIT. More specifically, if the channel gain falls below or goes over these thresholds, the channel will be allocated to WPT or WIT. Simulation results verify the performance of our proposed scheme.

Wireless powered communication (WPC) is able to provide wireless devices (WDs) practically infinite energy by using the radio frequency energy harvesting technique. The electricity of WDs for the wireless information transmission (WIT) is converted from the received electromagnetic signals of wireless energy transfer (WET). Power beacon (PB) is usually deployed as the dedicated energy source in WPC networks and the performance of WET is sensitive to the path-loss effect. Thus, both WET and WIT are significantly influenced by the locations of the PBs. To enable efficient transmission in WPC, this paper analytically investigates the impact of the PB deployment strategies on the WPC performance when WDs are clustered around the access points (APs). Specifically, we propose the PB deployment strategy based on the truncated Poisson cluster process (PCP) model. The distribution of PBs is correlated to the locations of WDs by choosing APs as their common parent points. Then, we derive the semi-closed form expressions for the energy outage probability and the transmission success probability. We further present the expressions of the meta distributions of WET and WIT, and investigate the proportion of the WDs in one cluster that achieves successful transmission while satisfying the reliability constraint. Moreover, the distance distribution between the WD and the intra-cluster PBs is analytically derived for the proposed correlated PCP model. By comparing the performance with other deployment strategies, it is shown that the preference of the PB deployment strategy depends on the PB density. The analytical and numerical results can provide insightful guidelines for designing practical WPC systems.

In this letter, the uplink (UL) wireless information transmission (WIT) and downlink (DL) wireless power transfer (WPT) in cell-free massive multiple-input multiple-output (CF-mMIMO) networks are investigated. Specifically, the mobile terminals (MTs) collect the radio-frequency energy emitted from the access points (APs) in the DL WPT phase and then use the harvested energy (HE) to transmit pilot and data symbols in the UL WIT phase. Considering the performance of CF-mMIMO networks with a large number of MTs is severely bottlenecked by pilot contamination, the superimposed pilot transmission (SPT) is advocated to alleviate its impact and improve transmission efficiency. Based on the SPT, closed-form UL achievable spectral efficiency (SE) and DL average HE expressions are derived. Simulation results verify the accuracies of the derived expressions and indicate that the SPT significantly outperforms the regular pilot transmission in terms of both SE and HE.

Nonlinear hydraulic coupling characteristics and energy conversion mechanism of pipeline - surge tank system of hydropower station with super long headrace tunnel

In this paper, we study the uplink (UL) and downlink (DL) ergodic capacity in the bidirectional dynamic network (BDN). By dynamically allocating the numbers of UL and DL remote radio heads (RRHs), BDN facilitates simultaneous UL and DL communications to accommodate the data traffic asymmetry. Assuming that the number of antennas at each RRH (M) is large, we derive the closed-form expressions for the ergodic achievable rates in BDN systems, and the theoretical results are shown to be accurate compared with the Monte Carlo simulation results. Furthermore, we investigate the performance of the limiting UL and DL rates when M goes to infinity, and it indicates that we can scale down the UL and DL power per user proportionally to 1/M to guarantee a certain UL or DL quality of service in BDN. Numerical results indicate that there exists an optimal ratio between UL and DL RRH numbers for the maximal spectral efficiency in BDN. Thanks to our proposed RRH layout which guarantees the uniformity and symmetry in the whole network, we can find the optimal ratio between UL and DL RRH numbers more easily.

In traditional half-duplex (HD) communication systems, the HD base station (BS) can transmit artificial noise (AN) to jam the eavesdroppers for securing the downlink (DL) communication. However, guaranteeing uplink (UL) transmission is not possible with an HD BS because HD BSs cannot jam the eavesdroppers during UL transmission. In this chapter, we investigate the resource allocation algorithm design for secure multiuser systems employing a full-duplex (FD) BS for serving multiple HD DL and UL users simultaneously. In particular, the FD BS transmits AN to guarantee the concurrent DL and UL communication security. We propose a multi-objective optimization framework to study two conflicting yet desirable design objectives, namely total DL transmit power minimization and total UL transmit power minimization. To this end, the weighted Tchebycheff method is adopted to formulate the resource allocation algorithm design as a multi-objective optimization problem (MOOP). The considered MOOP takes into account the quality-of-service (QoS) requirements of all legitimate users for guaranteeing secure DL and UL transmission in the presence of potential eavesdroppers. Thereby, secure UL transmission is enabled by the FD BS, which would not be possible with an HD BS. Although the considered MOOP is non-convex, we solve it optimally by semidefinite programming (SDP) relaxation. Simulation results not only unveil the trade-off between the total DL transmit power and the total UL transmit power, but also confirm that the proposed secure FD system can guarantee concurrent secure DL and UL transmission and provide substantial power savings over a baseline system.

Concurrent self-organization of coverage and capacity in both downlink (DL) and uplink (UL) is an ambitious task since 1) Coverage and capacity are conflicting key performance indicators (KPIs), and 2) an adequate DL performance does not necessarily entail an adequate UL performance because the DL and UL interference scenarios are fundamentally different. However, considering the UL when self-organizing the network is crucial because the UL transmission becomes more important due to the emergence of new applications and services, such as social networking, video calls, or sensor networks, which require either parity between DL and UL traffic or even more UL than DL traffic. In this paper, we propose a general concept for the self-organization of multiple KPIs while having only very sparse knowledge about the network. Using this concept, we propose an effective tilt-based algorithm that manages to jointly optimize coverage and capacity in DL and UL. In an urban scenario with real Long-Term Evolution (LTE) site locations, we were able to increase the cell-edge user throughput by 70% (DL) and 24% (UL) while concurrently decreasing the number of uncovered users by 21% (DL) and 25% (UL), compared with a well-chosen reference tilt setting.

In this paper, we find the optimum lengths of T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">UL</sub> , T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DL</sub> and B i.e. the uplink (UL) and downlink (DL) pilots and feedback bits respectively maximizing the sum of the lower bounds of the UL and the DL rates. With the aid of T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">UL</sub> symbols, the Base Station (BS) estimates the UL channel of each user. T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DL</sub> symbols are means of estimating the downlink channel, which after being normalized and quantized with B bits, is made available at the BS. Estimated Channel State Information (CSI) and quantized Channel Direction Information (CDI), which may be received erroneously, are thus available at the BS for computing the receive and the transmit Zero-forcing (ZF) filters, respectively. The use of ZF enables the derivation of analytical DL and UL mean squared error (MSE) expressions that give a lower bound on the DL and UL rates, respectively, needed for our optimization.

The paper proposes a receiver scheme for multicarrier-CDMA (MC-CDMA) that while not making use of the well known technique of guard interval is able to combat the effects of intersymbol as well as intercarrier interference (ISI, ICI). This is achieved by means of an adaptive multiple input multiple output (MIMO) fractionally spaced (FS) decision feedback equaliser (DFE) receiver scheme performing joint detection (JD). The forward section of the equaliser is designed to operate at a fractional rate, while the feedback section is symbol spaced. The analysis and design of the MIMO FS/DFE scheme is made for the minimum mean square error (MMSE) criterion. In this context, the steady state behaviour is analysed and the receivers performance are computed by means of the residual mean square error (MSE). Using Gaussian approximation an expression of the bit error rate (BER) for binary phase shift keying (BPSK) modulation is derived for both the down link (DL) and up link (UL) communication scenarios.

Full duplex (FD) communication has emerged as an attractive solution for increasing the network throughput, by allowing downlink (DL) and uplink (UL) transmissions in the same spectrum. However, only employing FD base stations in heterogeneous cellular networks (HCNs) cause coverage reduction, due to the DL and UL interferences as well as the residual loop interference. We, therefore, propose HCNs with half duplex massive multiuser multiple-input multiple-output macrocell base stations (MBSs) to relax the coverage reduction, and FD small cell base stations (SBSs) to improve spectrum efficiency. A tractable framework of the proposed system is presented, which allows to derive exact and asymptotic expressions for the DL and the UL rate coverage probabilities, and the DL and the UL area spectral efficiencies (ASEs). Monte Carlo simulations confirm the accuracy of the analytical results, and it is revealed that the equipping massive number of antennas at MBSs enhances the DL rate coverage probability, whereas increasing FD SBSs increases the DL and the UL ASEs. The results also demonstrate that by tuning the UL fractional power control, a desirable performance in both UL and DL can be achieved.

In this paper, we consider simultaneous wireless information and energy transfer in an orthogonal-frequency-division-multiple-access decode-and-forward relay network, in which an energy-constrained relay node harvests energy from a source node and uses the harvested energy to forward information to multiple destination nodes. Our objective is to maximize the end-to-end sum rate by resource allocation, subject to transmit power constraint at the source and energy-harvesting (EH) constraint at the relay. A non-convex and mixed-integer programming (MIP) problem is formulated to optimize time-switching (TS) ratios of EH and information decoding at the relay, TS ratio of information transmission from relay to destinations, subcarrier allocation as well as power allocation (PA) over all subcarriers at source and relay. We propose to decouple this problem into a convex problem and an MIP problem in fractional form. To solve the MIP problem, we transform it into an equivalent optimization problem in subtractive form which has a tractable solution. As a result, we propose a novel scheme to achieve jointly optimal TS ratios, subcarrier allocation and PA. Simulation results verify the optimality of our proposed resource allocation scheme.

Energy efficiency maximization in UAV communication networks with nonlinear energy harvesting

Wireless energy transfer (WET) is potentially a promising solution to provide convenient and reliable energy supplies for energy-constrained networks, and has drawn growing interests recently. To overcome the significant propagation loss over distance, employing multi-antennas at the energy transmitter (ET) to more efficiently direct wireless energy to desired energy receivers (ERs), termed energy beamforming, is an essential technique for WET. However, the achievable gain of energy beamforming crucially depends on the available channel state information (CSI) at the ET, which needs to be acquired practically. In this paper, we study the optimal design of one efficient channel-acquisition method for a point-to-point multiple-input multiple-output (MIMO) WET system, by exploiting the channel reciprocity based on which the ET estimates the CSI via dedicated reverse-link training from the ER. Considering the limited energy availability at the ER, the training strategy should be carefully designed so that the channel can be estimated with sufficient accuracy, and yet without consuming excessive energy at the ER. To this end, we propose to maximize the net energy at the ER, which is the total energy harvested offset by that used for channel training. The optimal training design, including the number of receive antennas to be trained, as well as the training time and power allocated, is derived. Our result shows that training helps only when the following conditions are satisfied: (i) the channel coherence time is sufficiently large; (ii) the number of antennas at the ET is large enough; and (iii) the effective signal-to-noise ratio (ESNR) is sufficiently high; otherwise, no training should be applied and isotropic energy transmission is optimal.

With simultaneous wireless information and power transfer, the energy of RF signal can be used effectively for the self-sustained operation of wireless devices. In practical applications, power splitting method can be used for simultaneous wireless information and power transmission (SWIPT) between base station and multi-user. Different user systems have different energy consumption, so users with insufficient power need more energy transmission to supplement their power. Nowadays, the beamforming strategy of simultaneous wireless information and energy transmission does not consider the problem of insufficient power at the terminal. This paper proposes a energy state feedback method to optimize simultaneous wireless information and power transmission system. Through the joint design optimization of beamforming and power splitting, the power transmission of users with insufficient power is added, and the minimized transmission power optimization is done under the conditions of satisfying SINR and energy harvesting constraints by utilizing the channel state information and node power information of each node. This optimization model is difficult to solve. In order to solve this problem, the concept of reserve group is introduced. When the optimization model cannot be solved, the users with the worst channel state of the node are put into the reserve group. These users do not participate in the optimization first. After the new channel state information is obtained, the optimization model is established again. If the problem can be solved, the transmission power of base station doesn’t reach the maximum power, some users in the reserve group is added to continue to optimize, if it has reached the maximum power of base station transmission, it is not optimizing, so as to maximize the optimization of all users and improve system performance.