Cooperative communication for wireless networks has gained a lot of recent interest due to its ability to mitigate fading with exploration of spatial diversity. In this paper, we study a joint optimization problem of ...Cooperative communication for wireless networks has gained a lot of recent interest due to its ability to mitigate fading with exploration of spatial diversity. In this paper, we study a joint optimization problem of jointly considering transmission mode selection, relay assignment and power allocation to maximize the capacity of the network through cooperative wireless communications. This problem is much more challenging than relay assignment considered in literature work which simply targets to maximize the transmission capacity for a single transmission pair. We formulate the problem as a variation of the maximum weight matching problem where the weight is a function over power values which must meet power constraints (VMWMC). Although VMWMC is a non-convex problem whose complexity increases exponentially with the number of relay nodes, we show that the duality gap of VMWMC is virtual zero. Based on this result, we propose a solution using Lagrange dual decomposition to reduce the computation complexity. We do simulations to evaluate the performance of the proposed solution. The results show that our solution can achieve maximum network capacity with much less computation time compared with exhaustive search, and our solution outperforms existing sub-optimal solutions that can only achieve much lower network capacity.展开更多
Cooperative communication through energy harvested relays in Cognitive Internet of Things(CIoT)has been envisioned as a promising solution to support massive connectivity of Cognitive Radio(CR)based IoT devices and to...Cooperative communication through energy harvested relays in Cognitive Internet of Things(CIoT)has been envisioned as a promising solution to support massive connectivity of Cognitive Radio(CR)based IoT devices and to achieve maximal energy and spectral efficiency in upcoming wireless systems.In this work,a cooperative CIoT system is contemplated,in which a source acts as a satellite,communicating with multiple CIoT devices over numerous relays.Unmanned Aerial Vehicles(UAVs)are used as relays,which are equipped with onboard Energy Harvesting(EH)facility.We adopted a Power Splitting(PS)method for EH at relays,which are harvested from the Radio frequency(RF)signals.In conjunction with this,the Decode and Forward(DF)relaying strategy is used at UAV relays to transmit the messages from the satellite source to the CIoT devices.We developed a Multi-Objective Optimization(MOO)framework for joint optimization of source power allocation,CIoT device selection,UAV relay assignment,and PS ratio determination.We formulated three objectives:maximizing the sum rate and the number of admitted CIoT in the network and minimizing the carbon dioxide emission.The MOO formulation is a Mixed-Integer Non-Linear Programming(MINLP)problem,which is challenging to solve.To address the joint optimization problem for an epsilon optimal solution,an Outer Approximation Algorithm(OAA)is proposed with reduced complexity.The simulation results show that the proposed OAA is superior in terms of CIoT device selection and network utility maximization when compared to those obtained using the Nonlinear Optimization with Mesh Adaptive Direct-search(NOMAD)algorithm.展开更多
基金supported by the National Basic Research 973 Program of China under Grant No. 2012CB315801the National Natural Science Foundation of China under Grant Nos. 61133015, 61003305, 61173167the Ph.D. Programs Foundation of Ministry of Education of China under Grant No. 20100161120022
文摘Cooperative communication for wireless networks has gained a lot of recent interest due to its ability to mitigate fading with exploration of spatial diversity. In this paper, we study a joint optimization problem of jointly considering transmission mode selection, relay assignment and power allocation to maximize the capacity of the network through cooperative wireless communications. This problem is much more challenging than relay assignment considered in literature work which simply targets to maximize the transmission capacity for a single transmission pair. We formulate the problem as a variation of the maximum weight matching problem where the weight is a function over power values which must meet power constraints (VMWMC). Although VMWMC is a non-convex problem whose complexity increases exponentially with the number of relay nodes, we show that the duality gap of VMWMC is virtual zero. Based on this result, we propose a solution using Lagrange dual decomposition to reduce the computation complexity. We do simulations to evaluate the performance of the proposed solution. The results show that our solution can achieve maximum network capacity with much less computation time compared with exhaustive search, and our solution outperforms existing sub-optimal solutions that can only achieve much lower network capacity.
文摘Cooperative communication through energy harvested relays in Cognitive Internet of Things(CIoT)has been envisioned as a promising solution to support massive connectivity of Cognitive Radio(CR)based IoT devices and to achieve maximal energy and spectral efficiency in upcoming wireless systems.In this work,a cooperative CIoT system is contemplated,in which a source acts as a satellite,communicating with multiple CIoT devices over numerous relays.Unmanned Aerial Vehicles(UAVs)are used as relays,which are equipped with onboard Energy Harvesting(EH)facility.We adopted a Power Splitting(PS)method for EH at relays,which are harvested from the Radio frequency(RF)signals.In conjunction with this,the Decode and Forward(DF)relaying strategy is used at UAV relays to transmit the messages from the satellite source to the CIoT devices.We developed a Multi-Objective Optimization(MOO)framework for joint optimization of source power allocation,CIoT device selection,UAV relay assignment,and PS ratio determination.We formulated three objectives:maximizing the sum rate and the number of admitted CIoT in the network and minimizing the carbon dioxide emission.The MOO formulation is a Mixed-Integer Non-Linear Programming(MINLP)problem,which is challenging to solve.To address the joint optimization problem for an epsilon optimal solution,an Outer Approximation Algorithm(OAA)is proposed with reduced complexity.The simulation results show that the proposed OAA is superior in terms of CIoT device selection and network utility maximization when compared to those obtained using the Nonlinear Optimization with Mesh Adaptive Direct-search(NOMAD)algorithm.