Transmit power and bits/channel use adaption in competitive cognitive radio networks

In this paper, we propose an optimization framework to determine the distribution of power and bits/channel use to secondary users in a competitive cognitive radio networks. The objectives of the optimization framework are to minimize total transmission power, maximize total bits/channel use and also to maintain quality of service. An upper bound on probability of bit error and lower bound on bits/channel use requirement of secondary users are considered as quality of service. The optimization problem is also constrained by total power budget across channels for a user. Simulating the framework in a centralized manner shows that more transmit power is required to allocate in a channel with higher noise power. However, allocation of bits/channel use is directly proportional to signal to interference plus noise power ratio. The proposed framework is more capable of supporting high bits/channel use requirement than existing resource allocation framework. We also develop the game theoretic user based distributed approach of the proposed framework. We see that user based distributed solution also follows centralized solution.     

Binary power allocation for cognitive radio networks with centralized and distributed user selection strategies

Motivated by the desire for efficient spectral utilization, we present a novel algorithm based on binary power allocation for sum rate maximization in Cognitive Radio Networks (CRN). At the core lies the idea of combining multi-user diversity gains with spectral sharing techniques and consequently maximizing the secondary user sum rate while maintaining a guaranteed quality of service (QoS) to the primary system. We consider a cognitive radio network consisting of multiple secondary transmitters and receivers communicating simultaneously in the presence of the primary system. Our analysis treats both uplink and downlink scenarios. We first present a distributed power allocation algorithm that attempts to maximize the throughput of the CRN. The algorithm is simple to implement, since a secondary user can decide to either transmit data or stay silent over the channel coherence time depending on a specified threshold, without affecting the primary users’ QoS. We then address the problem of user selection strategy in the context of CRN. Both centralized and distributed solutions are presented. Simulation results carried out based on a realistic network setting show promising results.     

Optimal downlink power allocation in cellular networks

In this paper, we introduce a novel approach for power allocation in cellular networks. In our model, we use sigmoidal-like utility functions to represent different users’ modulation schemes. Each utility function is a representation of the probability of successfully transmitted packets per unit of power consumed by a user, when using a certain modulation scheme. We consider power allocation with utility proportional fairness policy, where the fairness among users is in utility percentage i.e. percentage of successfully transmitted packets of the corresponding modulation scheme. We formulate our power allocation optimization problem as a product of utilities of all users and prove that it is convex and therefore the optimal solution is tractable. We present a distributed algorithm to allocate base station powers optimally with priority given to users running lower modulation schemes while ensuring non-zero power allocation to users running higher modulation schemes. Our algorithm prevents fluctuation in the power allocation process and is capable of traffic and modulation dependent pricing policy. This can be used to flatten traffic and decrease the service price for users. We also compare our results with a benchmark algorithm and show that our algorithm performs better in allocating powers fairly to all users without dropping any user in order to maximize performance.     

An energy efficient scheme by exploiting multi-hop D2D communications for 5G networks

The multi-hop Device-to-Device (M-D2D) communication has a potential to serve as a promising technology for upcoming 5G networks. The prominent reason is that the M-D2D communication has the potential to improve coverage, enhanced spectrum efficiency, better link quality, and energy-efficient communication. One of the major challenges for M-D2D communication is the mitigation of interference between the cellular user (CUs) and M-D2D users. Considering this mutual interference constraint, this work investigates the problem of optimal matching of M-D2D links and CUs to form spectrum-sharing partners to maximize overall sum rates of the cell under QoS and energy efficiency (EE) constraints. In this paper, we investigate the interference management for multi-hop (more than one-hop) D2D communication scenarios where we propose a channel assignment scheme along with a power allocation scheme. The proposed channel assignment scheme is based on the Hungarian method in which the channel assignment for M-D2D pairs is done by minimum interference value. The power allocation scheme is based on Binary Particle swarm optimization (BPSO). This scheme calculates the specific power values for all the individual M-D2D links. We have done a comprehensive simulation and the result portrays that our proposed scheme performs better compared to the previous work mentioned in the literature. The results clearly indicate that the proposed scheme enhances the EE of up to 13% by producing the optimal assignment of channels and power for the CUs and M-D2D users.     

Power control based on the Stackelberg game in two-tier femtocell networks

In this paper, the resource allocation strategy is investigated for a spectrum sharing two-tier femtocell networks, in which a central macrocell is underlaid with distributed femtocells. The spectral radius is introduced to address the conditions that any feasible set of users’ signal-to-interference-plus-noise ratio requirements should satisfy in femtocell networks. To develop power allocation scheme with the derived conditions, a Stackelberg game is formulated, which aims at the utility maximization both of the macrocell user and femtocell users. The distributed power control algorithm is given to reduce the cross-tier interference between the macrocell and femtocell with same channel. At last, admission control algorithm is proposed, aiming to exploit the network resource effectively. Numerical results show that the proposed resource allocation schemes are effective in reducing power consumption and more suitable in the densely deployed scenario of the femtocell networks. Meanwhile, it also presents that the distributed power allocation scheme combined with admission control can protect the performance of all active femtocell users in a robust manner.     

Macrocell–femtocells resource allocation with hybrid access motivational model

Femtocell technology has emerged as an efficient cost-effective solution not only to solve the indoor coverage problem but also to cope with the growing demand requirements. This paper investigates two major design concerns in two tier networks: resource allocation and femtocell access. Base station selection together with dual bandwidth and power allocation among the two tiers is investigated under shared spectrum usage. To achieve fair and efficient resource optimization, our model assumes that the hybrid access mode is applied in the femtocells. The hybrid access mode is beneficial for system performance as (1) it lessens interference caused by nearby public users, (2) it allows public users to connect to near femtocells and get better Quality of Service (QoS) and (3) it increases system capacity as it allows the macrocell to serve more users. However, femtocells’ owners can behave selfishly by denying public access to avoid any performance reduction in subscribers’ transmissions. Such a problem needs a motivation scheme to assure the cooperation of femtocells’ owners. In this paper, we propose a game-theoretical hybrid access motivational model. The proposed model encourages femtocells’ owners to share resources with public users, thus, more efficient resource allocation can be obtained. We optimize the resource allocation by means of the Genetic Algorithm (GA). The objective of the formulated optimization problem is the maximization of network throughput that is calculated by means of Shannon’s Capacity Law. Simulations are conducted where a modified version of the Weighted Water Filling (WWF) algorithm is used as a benchmark. Our proposed model, compared to WWF, achieves more efficient resource allocation in terms of system throughput and resources utilization.     

Multi-channel sensing and resource allocation in energy constrained cognitive radio networks

We consider a cognitive radio network in a multi-channel licensed environment. Secondary user transmits in a channel if the channel is sensed to be vacant. This results in a tradeoff between sensing time and transmission time. When secondary users are energy constrained, energy available for transmission is less if more energy is used in sensing. This gives rise to an energy tradeoff. For multiple primary channels, secondary users must decide appropriate sensing time and transmission power in each channel to maximize average aggregate-bit throughput in each frame duration while ensuring quality-of-service of primary users. Considering time and energy as limited resources, we formulate this problem as a resource allocation problem. Initially a single secondary user scenario is considered and solution is obtained using decomposition and alternating optimization techniques. Later we extend the analysis for the case of multiple secondary users. Simulation results are presented to study effect of channel occupancy, fading and energy availability on performance of proposed method.     

Joint user grouping and power allocation in VLC-NOMA system

With the energy consumption of wireless networks increasing, visible light communication (VLC) has been regarded as a promising technology to realize energy conservation. Due to the massive terminals access and increased traffic demand, the implementation of non-orthogonal multiple access (NOMA) technology in VLC networks has become an inevitable trend. In this paper, we aim to maximize the energy efficiency in VLC-NOMA networks. Assuming perfect knowledge of the channel state information of user equipment, the energy efficiency maximization problem is formulated as a mixed integer nonlinear programming problem. To solve this problem, the joint user grouping and power allocation (JUGPA) is proposed including user grouping and power allocation. In user grouping phase, we utilize the average of channel gain among all user equipment and propose a dynamic user grouping algorithm with low complexity. The proposed scheme exploits the channel gain differences among users and divides them into multiple groups. In power allocation phase, we proposed a power allocation algorithm for maximizing the energy efficiency for a given NOMA group. Thanks to the objective function is fraction form and non-convex, we firstly transform it to difference form and convex function. Then, we derive the closed-form optimal power allocation expression that maximizes the energy efficiency by Dinkelbach method and Lagrange dual decomposition method. Simulation results show that the JUGPA can effectively improve energy efficiency of the VLC-NOMA networks.     

Subchannel and power optimization for sum rate maximization in downlink multicarrier NOMA networks

In a multicarrier NOMA system, the subchannel allocation (SA) and power allocation (PA) are intricately linked and essential for improving system throughput. Also, for the successful execution of successive interference cancellations (SIC) at the receiver, a minimum power gap is required among users. As a result, this research comes up with optimization of the SA and PA to maximize the sum rate of the NOMA system while sticking to the minimum power gap constraint in addition to minimum user rate, maximum number of users in a subchannel and power budget constraints for downlink transmission in multicarrier NOMA networks. To ensure that the formulated problem can be solved in polynomial time, we propose solving it in two stages; SA followed by PA. To obtain SA, we investigate four algorithms: Greedy, WSA, WCA, and WCF. For PA, we propose a low-complexity algorithm. We compare the performance of the proposed method with benchmark method that does not consider the minimum power gap constraint. We conclude that employing WCF algorithm with the PA algorithm gives the best sum rate performance.     

Power allocation for cognitive underlay networks with spectrum band selection

In this paper, we study the cooperative communication of a cognitive underlay network by utilizing the diversity of multiple spectrum bands. In particular, we assume that the transmission power of the secondary user (SU) is subject to different joint constraints, such as peak interference power of the multiple primary users (PUs), peak transmission power of the SU, outage tolerate interference, and outage probability threshold. Accordingly, two power allocation schemes are considered on the basis of the minimum interference channel from the SU to the PU and the channel state information of the primary user link. Furthermore, the SU can select one of the three transmission modes following the channel state conditions, namely as cellular, device-to-device, or switching mode, to transmit the signal to the secondary user receiver. Given this setting, two power allocation schemes over a spectrum band selection strategy are derived. In addition, closed-form expressions for the outage probability of three modes are also obtained to evaluate the performance of the secondary network. Most importantly, a closed-form expression for the peak interference power level of the PU, which is considered as one of the most important parameters to control the SU’s transmission power, is derived by investigating the relation of two considered power allocation schemes in the practise. Finally, numerical examples show that the outage performance of secondary network in the switching mode outperforms the one of the cellular and device-to-device (D2D) mode for all considered power allocation schemes.     

Joint utility-based uplink power and rate allocation in wireless networks: A non-cooperative game theoretic framework

In this paper a novel utility-based game theoretic framework is proposed to address the problem of joint transmission power and rate allocation in the uplink of a cellular wireless network. Initially, each user is associated with a generic utility function, capable of properly expressing and representing mobile user’s degree of satisfaction, in relation to the allocated system’s resources for heterogeneous services with various transmission rates. Then, a Joint Utility-based uplink Power and Rate Allocation (JUPRA) game is formulated, where each user aims selfishly at maximizing his utility-based performance under the imposed physical limitations, and its unique Nash equilibrium is determined with respect to both variables, i.e. uplink transmission power and rate. The JUPRA game’s convergence to its unique Nash equilibrium is proven and a distributed, iterative and low complexity algorithm for computing JUPRA game’s equilibrium is introduced. The performance of the proposed approach is evaluated in detail and its superiority compared to various state of the art approaches is illustrated, while the contribution of each component of the proposed framework in its performance is quantified and analyzed.     

Spectrum efficient power allocation schemes for OFDM cognitive radio with statistical interference constraints

In this paper, we study the power allocation problem for an orthogonal frequency division multiplexing (OFDM)-based cognitive radio (CR) system. In a departure from the conventional power allocation schemes available in the literature for OFDM-based CR, we propose power allocation schemes that are augmented with spectral shaping. Active interference cancellation (AIC) is an effective spectral shaping technique for OFDM-based systems. Therefore, in particular, we propose AIC-based optimal and suboptimal power allocation schemes that aim to maximize the downlink transmission capacity of an OFDM-based CR system operating opportunistically within the licensed primary users (PUs) radio spectrum in an overlay approach. Since the CR transmitter may not have the perfect knowledge about the instantaneous channel quality between itself and the active PUs, the interference constraints imposed by each of the PUs are met in a statistical sense. We also study an optimal power allocation scheme that is augmented with raised cosine (RC) windowing-based spectral shaping. For a given power budget at the CR transmitter and the prescribed statistical interference constraints by the PUs, we demonstrate that although the on-the-run computational complexity of the proposed AIC-based optimal power allocation scheme is relatively higher, it may yield better transmission rate for the CR user compared to the RC windowing-based power allocation scheme. Further, the AIC-based suboptimal scheme has the least on-the-run computational complexity, and still may deliver performance that is comparable to that of the RC windowing-based power allocation scheme. The presented simulation results also show that both the AIC-based as well as the RC windowing-based power allocation schemes lead to significantly higher transmission rates for the CR user compared to the conventional (without any spectral shaping) optimal power allocation scheme.     

Cooperative spectrum sensing protocols and evaluation with IEEE 802.15.4 devices

Spectrum Sensing is one of the important tasks for wireless devices. By sensing the spectrum, wireless devices sense their radio environment and perform spectrum access accordingly to reduce collisions. Due to radio propagation effects and inherent noise in the measurements, performance of todays wireless technologies with individual spectrum sensing cannot solve the hidden node problem. Cooperative sensing is seen as a way to improve the performance of wireless devices improving the radio bandwidth utilization and minimizing interference among wireless devices. To the best of our knowledge, this is the first work which provides protocols for cooperative sensing and presents experimental results with IEEE 802.15.4 devices. We present and implement protocols and applications for primary, secondary and cooperative users with a dedicated control channel. Thereby, the secondary user receiver serves as a first cooperative node in the system which reduces collisions between primary and secondary users. We evaluate the system performance with receiver sensing and additional cooperative nodes. We also propose a mechanism to extend the protocol for multiple secondary users sharing the same control channel. Based on the evaluations, we also provide recommendations for usage of cooperative sensing with focus on IEEE 802.15.4.     

分布式光伏充电站Web实时监控平台设计

随着光伏充电站基础设施的广泛建设,为电动汽车用户提供便利的同时,也为其管理带来了巨大的挑战;为了实现对光伏充电站更加有效的管理,在分析分布式光伏充电站数据通信方案的基础上,设计了一种光伏充电站Web实时监控平台;该平台基于ZigBee技术、GPRS-DTU技术、HTTP协议设计了直流充电桩无线传感器数据采集方案,部署数据库服务器、Web服务器以克服充电站无人值守的问题,实现对该分布式系统的集中管控,同时设计用于充电预约、监控、提醒等功能的安卓用户APP以提升用户体验,并对该系统进行实验验证;经验证,该设计方案能够有效实现对分布式光伏充电站的实时数据采集与Web端集中管控,为充电站无人值守与远程监控提供了一种有效的技术解决方案。     

A cognitive MAC protocol for QoS provisioning in ad hoc networks

In this paper, we consider an ad hoc network overlaying a legacy time-division multiple access (TDMA) system. This kind of ad hoc and infrastructure-based coexisting architecture can have an important application for the future cognitive radio (CR) network. To establish an overlaying ad hoc network in the presence of primary users, the medium access control (MAC) protocol shall achieve high spectrum utilization, avoid interfering the primary user and establish the link quickly. To this end, we propose four enhanced mechanisms for the carrier sense multiple access with collision avoidance (CSMA/CA) MAC protocol: (1) a neighbor list establishment mechanism for recognizing spectrum usage opportunities, (2) a set of contention resolution methods to reduce the collision and delay variance, (3) an invited reservation procedure for meeting the delay requirements of real-time traffic, and (4) a distributed frame synchronization mechanism for coordinating transmission without a centralized controller. Compared to the legacy IEEE 802.11 MAC protocol, the proposed CSMA/CA MAC protocol enhancement can improve the system throughput by 50% through analysis and NS-2 simulations, while keeping the dropping rate lower than 2% for delay-sensitive traffic. Furthermore, the standard deviation of the access delay is reduced by five times. With these QoS enhanced mechanisms, the proposed cognitive CSMA/CA MAC protocol can allow an ad hoc network to coexist with the legacy TDMA system.     

Physical layer security performance of NOMA-assisted vehicular communication systems over double-Rayleigh fading channels

In this paper, we investigate the secrecy performance of a downlink non-orthogonal multiple access enabled V2V communication system wherein a source vehicle communicates with two authenticated user vehicles, i.e., far user and near user, in the presence of a passive eavesdropper vehicle. Moreover, we formulate two scenarios based on the eavesdropper’s decoding capabilities; (1) Scenario I: when the eavesdropper vehicle has comparable decoding capabilities as with the authorized user vehicles, and (2) Scenario II: when the eavesdropper is entirely capable of perfectly decoding the signals from both authorized user vehicles. For such a system configuration with Scenarios I & II, we deduce the analytical expressions for the secrecy outage probability (SOP) and ergodic secrecy capacity over independent but not necessarily identically distributed double-Rayleigh fading channels. Further, to obtain insights into the secrecy diversity order for the legitimate user vehicles under Scenarios I & II, we present the asymptotic SOP analysis by taking three cases into account; (1) Case 1: when the average transmit signal-to-noise ratio approaches infinity, (2) Case 2: when the average channel gains of the user vehicles tend to infinity with fixed average channel gains corresponding to the eavesdropper, and (3) Case 3: when the average channel gains pertaining to the user vehicles and the eavesdropper tend to infinity. From which, we can infer that the secrecy diversity order of the far user vehicle is zero for Cases 1, 2, & 3, whereas the secrecy diversity order of the near user vehicle is zero for Cases 1 & 3 and one for Case 2, under Scenarios I & II. The numerical and simulation results corroborate our theoretical investigations. Our results demonstrate the impact of transmit power, power allocation factor, channel conditions of legitimate users and eavesdropper on the system’s secrecy performance.     

Fault-tolerant Remote Quantum Entanglement Establishment for Secure Quantum Communications

This work presents a strategy for constructing long-distance quantum communications among a number of remote users through collective-noise channel. With the assistance of semi-honest quantum certificate authorities (QCAs), the remote users can share a secret key through fault-tolerant entanglement swapping. The proposed protocol is feasible for large-scale distributed quantum networks with numerous users. Each pair of communicating parties only needs to establish the quantum channels and the classical authenticated channels with his/her local QCA. Thus, it enables any user to communicate freely without point-to-point pre-establishing any communication channels, which is efficient and feasible for practical environments.     

Network sum-rate maximization via joint power allocation and antenna selection for clustered downlink/uplink NOMA networks

This paper considers the problem of joint power allocation and antenna selection (J-PA-AS) for downlink (DL) and uplink (UL) clustered non-orthogonal multiple-access (NOMA) networks. In particular, the goal is to perform antenna selection for each user cluster and allocate transmit power to its users so as to maximize the network sum-rate in the DL and UL directions, while satisfying quality-of-service (QoS) requirements. The formulated problem happens to be non-convex and NP-hard, and thus, there is no systematic or computationally-efficient approach to solve it directly. In turn, a low-complexity two-stage algorithm is proposed. Specifically, the first stage optimally solves the sum-rate maximizing power allocation for each (antenna, user cluster) pair. After that, antenna selection is optimally solved in polynomial-time complexity via the Kuhn–Munkres with backtracking (KMB) algorithm. Extensive simulation results are provided to validate the proposed algorithm, which is shown to efficiently yield the optimal network sum-rate in each link direction, in comparison to the optimal J-PA-AS scheme (solved via a global optimization package), and superior to other benchmark schemes. Light is also shed on the impact of spatial-diversity on the network sum-rate, where it is shown that the greater the number of base-station antennas is, the higher the network sum-rate, and the lower the outage events. Additionally, the significance of decoupling antenna selection in each link direction on the network sum-rate is highlighted. Lastly, the cases of imperfect channel state information (CSI) and imperfect successive interference cancellation (SIC) have been investigated, where it is demonstrated that spatial-diversity gains reduce the adverse effects of imperfect CSI and SIC on the network sum-rate.     

Cooperative communication with imperfect channel information: Performance analysis and optimum power allocation

In this paper, symbol-error-rate (SER) performance analysis is provided for decode-and-forward (DF) and amplify-and-forward (AF) cooperation schemes in wireless networks with imperfect channel information. We derive closed-form SER formulations for a single relay system with square MQAM signals in a flat Rayleigh fading channel. Moreover, closed-form and high SNR tight SER approximations are established to show the asymptotic performance of the cooperation protocols. Simulations and comparisons verify that these approximations lead to similar results to those from the exact SER formulations for different power allocation methods. Furthermore, based on these SER performance analyses, we determine the optimum power allocation for the AF and DF cooperation scenarios.