Non-Cooperative Game Theoretic Power Allocation Strategy for Distributed Multiple-Radar Architecture in a Spectrum Sharing Environment

This paper studies the case of an overlay cognitive radio network where the primary user leases spectral resources to the secondary user in exchange for cooperation, considering that both type of users have specific quality of service requirements. We investigate the problem of joint power and time allocation for the secondary access during the cooperative phase, with a view to optimizing the effective capacity of the primary user given an average energy constraint for the secondary user. Afterwards, the optimal power allocation of the secondary user for its own transmission phase is investigated in order to maximize the effective capacity of the secondary link. The proposed joint power and time allocation mechanism is compared with an optimal time/constant power allocation scheme and a less sophisticated baseline allocation scheme, i.e. power allocation under constant time and its superiority is proven for various network parameters. The reference model of one primary---one secondary user is extended to a general multi user cognitive radio network through the proposed pairing mechanism based on matching theory. Particularly, considering the remarks of the reference scenario, we propose two different matching schemes (with/without consideration of primary users' quality of service requirements) and we confirm their superiority compared to other matching mechanisms.

Joint resource and trajectory optimization in a UAV-enabled dual-function radar-communication network

This paper investigates the problem of low probability of intercept-based optimal power allocation (LPI-OPA) for an integrated multistatic radar and communication system, which consists of multiple transmitters operating at different frequencies, a radar receiver, and a communication receiver (CR). The integrated multistatic radar and communication system is capable of fulfilling the requirements of both radar and communication subsystems. The key tenet of the integrated system is to minimize the total power consumption by optimizing the transmit power allocation at each transmitter for radar waveforms and information signals, which is constrained by a predetermined target detection performance for the RR and a desired information rate for the CR. Since the analytical closed-form expression of the probability of detection is not tractable, its upper bound is derived. We analytically show that the resulting optimization problem can be reformulated as two subproblems, which can be solved by an efficient solution procedure based on the approach of linear programming and the Karush–Kuhn–Tuckers optimality conditions. Simulation results are provided to show that the LPI performance of the integrated multistatic radar and communication system can significantly be enhanced by employing our proposed LPI-OPA scheme.

In this paper, a power allocation space-time coding scheme based on the self-coding property of residual loop interference (RLI) for two-way full-duplex (FD) amplify-and-forward (AF) relaying networks is proposed. The relay and direct link cooperate to forward the received signals to destination node, forming the self-coded distributed space-time code, in which the relay performs self-coding using the RLI after implementing some self-interference cancellation techniques. Then, an iterative power allocation algorithm is presented. With the proposed power allocation algorithm, both amplifying factor and transmit powers of terminal nodes are jointly optimized to maximize the smaller signal-to-interference-plus-noise ratio (SINR) of terminal nodes under a total power constraint when estimated instantaneous channel state information is available. We theoretically demonstrate the benefits of the proposed power allocation algorithm compared to equal power allocation. Simulation results show that the proposed scheme achieves significant improvement in performance compared with existing schemes for FD relaying systems and half-duplex relaying systems.

To satisfy the increasing demands for high data-rate service of high-speed railway (HSR) users on the train, the most promising approach is to utilize the two-hop architecture. With this architecture, large amount of data will be transferred to the access point (AP) at which some data may need to be cached when the train approaches the cell edge. In this paper, an energy-efficiency buffer (EEB) power allocation scheme is proposed, which is able to achieve a high energy efficiency under the requirement of buffer size in HSR scenarios. Firstly, the energy-efficiency optimization problem is formulated as a fractional form. Secondly, this non-convex problem is resolved by transforming it into an equivalent one. Then an iterative power allocation algorithm is proposed and the optimal solution is obtained based on it. Finally, we analyze the effect of cache point on energy efficiency (EE) performance of the proposed EEB power allocation scheme. Furthermore, the relationship between the buffer size and EE performance of HSR communication system is presented. Simulation results suggest that the proposed EEB power allocation scheme can achieve the optimal energy-efficient performance.

Allocations of physical transmission rate, sub-carrier, and power in MC-CDMA systems are proposed to minimize total uplink power consumptions for users of different data rate and bit-error-rate (BER) requirements with the receiver using linear minimum-mean-square-error (LMMSE) MUD. Based on multi-code (MC) and variable-spreading-length (VSL) strategies for multi-rate transmissions, we derive the discrete-rate transmission capacity of MC-CDMA and propose a simple admission control criterion for users of individual quality-of-service (QoS) demands. This criterion linearly relates the code length with the transmission rate and BER requirements of all users. An iterative power allocation algorithm is proposed after deciding all supportable transmission rates to allocate the sub-carrier power of each user and jointly solve the sub-carrier allocation problem. The results show that in either MC MC-CDMA or VSL MC-CDMA, the most power-efficient allocation is to distribute the power of each user over several sub-carriers of better quality and even concentrate on the best one, if it is exclusive

To promote future intelligent systems, a novel cyber-physical-social smart system (CPS3) powered by the Internet of Things is presented in this paper, where wireless network virtualization is adopted to enhance the diversity and the flexibility of the service operation and the system management. Based on the presented system, a robust energy-efficient resource allocation scheme is proposed to guarantee the outage probability requirements of controllers and actuators while realizing the maximization of the system energy efficiency. Different from the existing works, imperfect channel state information is studied for energy-efficient resource allocation in CPS3. To effectively handle the formulated optimization problem, the concept of virtual devices is introduced to equivalently reformulate the original problem. Afterward, the probabilistic mixed problem is approximately transformed into a nonprobabilistic problem though outage probability analyses. After the transformation, the optimization problem can be decomposed into power allocation and channel allocation, where an iterative algorithm for power allocation is adopted to maximize the system energy, and a heuristic greedy algorithm is presented to schedule sensors and actuators on different subchannels based on the obtained power allocation results. Simulation results demonstrate the convergency of the proposed algorithm and the advantages of the proposed scheme.

In this article, we address the problem of optimal joint power and resource allocation when Non-Orthogonal Multiple Access (NOMA) and Orthogonal Frequency Multiple Access (OFDMA) are combined for a hybrid downlink multiple access. First, an optimal solution of joint power and resource allocation minimizing the transmit power consumption, is obtained by rewriting the original optimization problem into an equivalent convex one and then by solving it by means of the well-known interior-point method. Second, we analyze the properties of the optimum, which are twofold; we show that at the optimum, the order of the users is preserved from one channel to another. Then, we derive a closed-form expression for the optimal power allocation in the particular case where all users have positive non-zero transmit powers in all channels.

Interference-aware channel assignment and power allocation for device-to-device communication underlaying cellular network

A novel multibeam satellite system design is proposed in this paper based on jointly optimizing power and carrier allocation in order to best match the asymmetric traffic requests. This design introduces higher and asymmetric interference levels throughout the coverage. However, both power and bandwidth will be used more efficiently. Even though the problem of power and bandwidth allocation has been addressed in terrestrial wireless communications, it is new in satellite systems and since architecture and channel are different, available results and algorithms are not applicable to satellite payload systems. In this paper we formulate the resource allocation problem as max-min SINR balancing based on the recently introduced axiomatic-based interference model, but in addition, we also optimize the carrier allocation when performing the SINR balancing problem. An analytical solution for the optimal carrier allocation is proposed and we iteratively find the optimal power allocation for each beam. The Shannon (upper bound) and current state-of-the art PHY layer technology: DVB-S2 are proposed to be implemented in order to obtain the gap between them. Simulation results show significant improvements in terms of power gain, spectral efficiency and traffic matching ratio comparing with conventional system, which is designed based on uniform bandwidth and power allocation.

Cognitive radio and heterogeneous wireless networks are important candidate techniques for the fifth generation (5G) communication systems. On the other hand, propagation properties of radio channels in a physical layer are exploited to design efficient secure transmission schemes for 5G wireless networks. In this work, a security-aware joint power and subchannel allocation problem based on the inter-network cooperation is investigated at cognitive heterogeneous networks via imperfect spectral sensing. The security-aware joint power and subchannel allocation is subject to constraints in available subchannels, proportional fairness secrecy transmission rates among secondary mobile terminals (MTs), total interference power threshold, and total power for each secondary MT. In order to determine the impact of imperfect spectral sensing to resource allocation, we first represent the interference power at primary base station in terms of the misdetection probability and false alarm probability. Then, the security-aware power and subchannel allocation problem with inter-network cooperation is formulated as a biconvex optimization problem, and an optimal security-aware power and subchannel allocation algorithm is proposed utilizing the dual decomposition method. Compared to the heuristic power and subchannel allocation algorithms, numerical simulation results show that the proposed algorithms improve the total secrecy throughput and guarantee the proportional fairness among different secondary MTs.

In spatial modulation (SM) systems, when channel state information is available at the transmitter, adaptive power allocation can be exploited to enhance the SM performance. In this paper, optimal power allocation in SM systems is considered from an information-theoretical view. First, as there is no closed-form expression of the SM capacity, the instantaneous mutual information is formulated in an analytic form for SM systems with two transmit antennas. Then, two power-allocation algorithms are proposed to maximize the SM mutual information. One is a sub-optimal power-allocation algorithm that is established in closed form to maximize the upper bound of SM mutual information. The other is an iterative algorithm for optimal power allocation that is proposed to achieve the maximum mutual information of SM systems while dramatically reducing the operational complexity compared with global computer searching. To evaluate the performance of the proposed power-allocation algorithms, numerical and simulation results are reported in terms of outage capacity and ergodic capacity, which demonstrates that the proposed power-allocation algorithms significantly improve the SM performance, compared with conventional equal-power allocation.

This paper investigates the optimal resource allocation of a downlink non-orthogonal multiple access (NOMA) system consisting of one base station and multiple users. Unlike existing short-term NOMA designs that focused on the resource allocation for only the current transmission timeslot, we aim to maximize a long-term network utility by jointly optimizing the data rate control at the network layer and the power allocation among multiple users at the physical layer, subject to practical constraints on both the short-term and long-term power consumptions. To solve this problem, we leverage the recently-developed Lyapunov optimization framework to convert the original long-term optimization problem into a series of online rate control and power allocation problems in each timeslot. The power allocation problem, however, is shown to be non-convex in nature and thus cannot be solved with a standard method. However, we explore two structures of the optimal solution and develop a dynamic programming based power allocation algorithm, which can derive a globally optimal solution, with a polynomial computational complexity. Extensive simulation results are provided to evaluate the performance of the proposed joint rate control and power allocation framework for NOMA systems, which demonstrate that the proposed NOMA design can significantly outperform multiple benchmark schemes, including orthogonal multiple access (OMA) schemes with optimal power allocation and NOMA schemes with non-optimal power allocation, in terms of average throughput and data delay.

In this letter, we address the problem of energy efficient coordinated power allocation in a multicell distributed antenna system (DAS). Due to the mutual coupling of multiple cells caused by intercell interference (ICI), the problem is nonconvex and, therefore, is difficult to solve. We assume that only the large-scale channel state information at the transmitter (CSIT) is known to reduce the system cost. Using successive Taylor expansion, we formulate the problem as a series of quasi-concave fractional programming subproblems. These subproblems are further solved using an iterative power allocation algorithm. The proposed solution is superior to existing methods, as verified by simulation results.

The cognitive radio technology aims to increase the spectrum utilization by accessing opportunistically the unused spectrum bands. Multicarrier communications are considered to be used in cognitive radio systems. In cognitive radio systems, the power allocation should be carried out within the cognitive radio network so that no excessive interference is caused to the primary user. In this paper, an iterative power allocation algorithm is proposed to maximize the downlink capacity of the cognitive radio system under both the total power budget and interference introduced to the primary user constraints. Moreover, two complexity reduced algorithms are presented. The problem of channel allocation in multiuser cognitive radio networks is discussed. Finally, the performance of the proposed algorithms is investigated using computer simulations.KeywordsCognitive RadioPower AllocationOrthogonal Frequency Division Multiplex SystemCognitive Radio SystemSubcarrier AllocationThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.