Power allocation in cooperative MIMO systems under individual power constraints

allocation （PA） plays an important role in capacity improvement for cooperative multiple-input multipleoutput （Co-MIMO） systems. Many contributions consider a total power constraint （TPC） on the sum of transmit power from all nodes in addressing PA problem. However, in practical implementations, each transmit node is equipped with its own power amplifier and is limited by individual power constraint （IPC）. Hence these PA methods under TPC are not realizable in practical systems. Meanwhile, the PA problem under IPC is essential, but it has not been studied. This paper extends the traditional non-cooperative water-filling PA algorithm to IPC-based Co-MIMO systems. Moreover, the PA matrix is derived based on the compound channel matrix from all the cooperative nodes to the user. Therefore, the cooperative gain of the IPC-based Co-MIMO systems is fully exploited, and further the maximal instantaneous capacity is achieved. Numerical simulations validate that, under the same IPC conditions, the proposed PA scheme considerably outperforms the non-cooperative water-filling PA and uniform PA design in terms of ergodic capacity.

An Energy-Efficient Wireless Power Transmission-Based Forest Fire Detection System

Compared with the traditional techniques of forest fires detection,wireless sensor network(WSN)is a very promising green technology in detecting efficiently the wildfires.However,the power constraint of sensor nodes is one of the main design limitations of WSNs,which leads to limited operation time of nodes and late fire detection.In the past years,wireless power transfer(WPT)technology has been known as a proper solution to prolong the operation time of sensor nodes.In WPT-based mechanisms,wireless mobile chargers(WMC)are utilized to recharge the batteries of sensor nodes wirelessly.Likewise,the energy of WMC is provided using energy-harvesting or energy-scavenging techniques with employing huge,and expensive devices.However,the high price of energy-harvesting devices hinders the use of this technology in large and dense networks,as such networks require multiple WMCs to improve the quality of service to the sensor nodes.To solve this problem,multiple power banks can be employed instead of utilizing WMCs.Furthermore,the long waiting time of critical sensor nodes located outside the charging range of the energy transmitters is another limitation of the previous works.However,the sensor nodes are equipped with radio frequency(RF)technology,which allows them to exchange energy wirelessly.Consequently,critical sensor nodes located outside the charging range of the WMC can easily receive energy from neighboring nodes.Therefore,in this paper,an energy-efficient and cost-effective wireless power transmission(ECWPT)scheme is presented to improve the network lifetime and performance in forest fire detection-based systems.Simulation results exhibit that ECWPT scheme achieves improved network performance in terms of computational time(12.6%);network throughput(60.7%);data delivery ratio(20.9%);and network overhead(35%)as compared to previous related schemes.In conclusion,the proposed scheme significantly improves network energy efficiency for WSN.

Solution of Combined Heat and Power Economic Dispatch Problem Using Genetic Algorithm

This research proposes a synergistic meta-heuristic algorithm for solving the extreme operational complications of combined heat and power economic dispatch problem towards the advantageous economic outcomes on the cost of generation. The combined heat and power (CHP) is a system that provides electricity and thermal energy concurrently. For its extraordinary efficiency and significant emission reduction, it is considered a promising energy prospect. The broad application of combined heat and power units requires the joint dispatch of power and heating systems, in which the modelling of combined heat and power units plays a vital role. The present research employs the genetic optimization algorithm to evaluate the cost function, heat and power dispatch values encountered in a system with simple cycle cogeneration unit and quadratic cost function. The system was first modeled to determine the various parameters of combined heat and power units towards solving its economic dispatch problem directly. In order for modelling to be done, a general structure of combined heat and power must be defined. The test system considered consists of four units: two conventional power units, one combined heat and power unit and one heat-only unit. The algorithm was applied to test system while taking into account the power and heat units, bounds of the units and feasible operation region of cogeneration unit. Output decision variables of 4-unit test systems plus cost function from Genetic Algorithm (GA), was determined using appropriate codes. The proposed algorithm produced a well spread and diverse optimal solution and also converged reasonably to the actual optimal solution in 51 iterations. The result obtained compared favourably with that obtained with the direct solution algorithm discussed in a previous paper. We conclude that the genetic algorithm is quite efficient in dealing with non-convex and constrained combined heat and power economic dispatch problem.

Energy-Efficient Static Data Collector-based Scheme in Smart Cities

In the Internet of Things(IoT)-based smart city applications,employing the Data Collectors(DC)as the data brokers between the nodes and Base Station(BS)can be a promising solution to enhance the energy efficiency of energy-constrained IoT sensor nodes.There are several schemes that utilize mobile DCs to collect the data packets from sensor nodes.However,moving DCs along the hundreds of thousands of sensors sparsely distributed across a smart city is considered a design challenge in such schemes.Another concern lies in how these mobile DCs are being powered.Therefore,to overcome these limitations,we exploit multiple energy-limited Static Data Collectors(SDC)which are deployed at the locations optimized so that the energy consumption of both nodes and SDCs is minimized.Likewise,anUnmannedAerial Vehicle(UAV)-enabled wireless power transfer is considered for sustaining the SDCs to avoid their energy depletion and data packet loss.The sustainable charging process operates periodically in each cycle so that the UAV flies from a charging station and after recharging the SDCs,it comes back to the station to be recharged.In this study,we formulate a problem to optimize the movement trajectory and charging time of UAV so that sustainable operation of SDCs during a cycle can be achieved.Unlike the prior studies,our proposed scheme determines the optimal trajectory and charging time at the beginning of each cycle which leads to increase accuracy in comparison with long-term optimization-based schemes.The outcomes of simulation experiments show that the proposed scheme achieves improved network performance in terms of data delivery ratio(12.5%);system throughput(6.6%);total energy consumption(59.19%);and network lifetime(58%)as compared to previous related works.

Power allocation for collaborative transmission in LTE-Advanced

Collaborative transmission among evolved Node-Bs(eNBs)is one of the promising techniques for LTE-Advanced to provide broader coverage and higher spectral efficiency.The interference among multi-cell transmission can be mitigated by joint precoding,such as multi-cell block diagonalization(BD)at cooperative eNBs.The major difference between multi-cell and single-cell transmission is that the power constraint has to be considered on a per-eNB basis.To satisfy per-eNB power constraint(PePC),a simplified power allocation algorithm for the multi-cell BD based collaborative transmission is proposed in this paper.The algorithm provides a power allocation coefficient matrix for BD to meet PePC.Simulation results demonstrate that the proposed algorithm has a near-optimal performance with simplicity.

Comparison of downlink transmission strategies for distributed antenna systems with multi-antenna arrays

In multi-user distributed antenna systems （DAS）, the scenario where each distributed antenna port is a multi-antenna array has not been comprehensively studied. In this article, four simple extended methods for downlink transmission are analyzed and compared in this scenario, two of which are based on the block diagonalization （BD） algorithm, namely joint BD and intra BD method. The other two methods are joint time division multiplexing （TDM） method and central antenna system （CAS） method. These four methods are evaluated through both theoretic analysis and insightful simulations. The theoretic analysis includes the receiving signal combination, post-processing signal to interference plus noise ratio （SINR） calculation. It shows that the intra BD method requires less channel state information at the transmitter （CSIT） and has lower computational complexity and process latency. Simulation results show that the joint BD method provides the best performance, and the intra BD method suffers little performance loss. Overall, the intra BD method is proved to be an optimal tradeoff which achieves high capacity, especially for the cell edge users, with relatively low complexity when power constraints are considered.