Transmit Power Allocation Scheme Research Articles

Cooperative jamming aided securing wireless communications without CSI of eavesdroppers

Physical layer security was designed as an effective solution to provide the security and confidentiality of information transmission in wireless networks, and secrecy transmission capacity (STC) played a key role in analyzing the impact of system parameters on physical layer security. Different from the previous works, which exploited cooperative jamming to improve the security with the assumption of perfect channel state information (CSI) of eavesdroppers (Eves), in this paper, without considering Eves’ CSI, we designed two secrecy improvement strategies aided by cooperative jamming with transmit power allocation scheme, i.e., connection guard zone (CGZ) and improved interferer protected zone (IIPZ). Specifically, we established an analytical framework of the STC by applying the tools of stochastic geometry and derived conditions that achieved a positive STC. In addition, we consider the impact of Random WayPoint (RWP) mobile receiver and active eavesdroppers on physical layer security. Simulations showed that IIPZ achieves the best reliability performance and CGZ makes the best secrecy performance than existing popular protections, and RWP mobile destination can achieve a higher level of reliability and STC than these achievable in static scenarios.

Energy-Efficient Wireless System Within Average Delay and With Mixed-Erlang-Distributed Data

Energy efficiency (EE) is a key performance indicator in modern wireless systems. Consider a point-to-point buffer-aided communication system model, where 1) the wireless channel has Shannon capacity and is characterized by the Nakagami-m distribution; 2) application data has an average data rate with mixed-Erlang distributed data sizes and a quality-of-service (QoS) constraint on average delay. In this letter, we first develop a numerical expression of average delay in the above system model, and then propose an optimal transmit power allocation scheme to maximize the EE under the QoS constraint. It is shown in the Monte-Carlo simulation that our numerical expression can accurately approximate the average delay. From the numerical simulation, the maximum EE as a function of data rate is shown to have a bell-shaped curve.

D2D Communication Network Interference Coordination Scheme Based on Improved Stackelberg

The sudden explosive growth of data in intelligent devices and existing communication networks has brought great challenges to existing communication networks. On the one hand, D2D (device to device) technology greatly improves the utilization of spectrum resources; on the other hand, it improves the communication quality of users. It has become an important part of the future communication network. Aiming at the problem that the existing D2D communication network system has complex user interference, and the communication quality of cellular users is difficult to guarantee, a D2D communication network interference coordination scheme based on improved Stackelberg is proposed. Using resource allocation and power control to solve the interference coordination problem, this paper proposes an improved Stackelberg model based on DQN (deep Q network), establishes the master–slave game between cellular users and multiplexing resource users (D2D users; relay communication users), optimizes the cost parameters in the Stackelberg mode and improves the transmission power and resource allocation scheme of multiplexing resource users. The simulation results show that compared with similar algorithms, the algorithm proposed in this paper has the best performance in guaranteeing the QoS of cellular users in the system and has good interference management capability for D2D communication networks.

Concurrent multi-beam transmissions for reliable communication in millimeter-wave networks

Millimeter-wave (mmWave) communication is an important technology to meet the demand of high data rate in sixth generation (6G) wireless networks. Blockage is a major obstacle to reliable transmissions for mmWave communication. In order to prevent complete blocking of concurrent multiple beams and measure the reliability of concurrent multi-beam transmissions, beam space isolation degree (BSID) and reliability coefficient are defined, based on which a joint multi-beam selection and transmission power allocation scheme that maximizes the tradeoff utility of instantaneous achievable rate and reliability. We break the original optimization problem into two subproblems (i.e., multi-beam selection subproblem and transmission power allocation subproblem) to reduce the computational complexity, and solve them iteratively until no further improvement of the system utility, where exact potential game is used to solve the former under fixed transmission power policy, and first-order Taylor expansion and Lagrangian multiplier algorithm are utilized to solve the latter under fixed concurrent multi-beam selection strategy. Evaluation results indicate that the proposed scheme provides better sum utility and sum reliability with lower complexity, which indicates that concurrent multi-beam transmissions can improve the reliability of mmWave communication.

Joint Device Pairing, Reflection Coefficients, and Power Control for NOMA Backscatter Systems

Non-orthogonal multiple access (NOMA) and backscatter communication are two emerging technologies for low-power communication. In this paper, we consider a NOMA backscatter system, where signals from two backscatter devices are multiplexed on a frequency resource block using NOMA in each time slot. Our objective is to maximize the average energy efficiency by optimizing backscatter device pairing, reflection coefficients of backscatter devices, and the transmit power of the reader. We formulate the average energy efficiency maximization problem subject to the minimum circuit power and the minimum data rate requirements of the backscatter devices, and the transmit power constraint of the reader. The formulated problem is nonconvex. To obtain a suboptimal solution for this problem, we use alternating optimization technique and decompose the problem into two subproblems. The subproblems are solved by using fractional programming, Dinkelbach’s algorithm, and successive convex approximation method. Simulation results show that our proposed algorithm converges quickly to a suboptimal solution. Our proposed algorithm outperforms several baseline algorithms, including the genetic algorithm, fixed device pairing scheme, conventional device pairing scheme, maximum transmit power allocation scheme, and random reflection coefficient selection scheme, in terms of the average energy efficiency. The optimality gap of our proposed algorithm is investigated by comparing with the optimal scheme, in which the optimal device pairing is obtained based on exhaustive search.

Optimized Over-the-Air Computation for Wireless Control Systems

The over-the-air controller was recently proposed to enable efficient computation of the control signal for control systems, by leveraging the over-the-air computation concept. This letter introduces a transmit power allocation scheme for the over-the-air controller, where the wireless channel directly produces the control gain of a discrete-time linear control system. The proposed design scheme essentially minimizes the worst effect of the channel noise to the desired control system output, subject to the transmit power limit over the wireless channel. Despite the non-convexity of the problem, we derive the control cost criterion as linear matrix inequalities with transmit power constraints. We comprehensively investigate the control performance and the transmit power cost of the proposed scheme in various scenarios. The proposed optimization scheme shows significant control performance gain against the state-of-the-art solution, while having a comparable transmit power consumption.

Transmit Power Allocation Schemes for Performance Improvement of Poor Conditioned End Devices in LPWAN

This paper studies the performance improvement of end devices with a low received signal strength indicator, that is, the poor condition, in general low power wide area networks (LPWANs). To improve the performance, we discuss the transmit power allocation utilizing the benefit of the capture effect, which results in an advantage depending on the signal-to-noise ratio and signal-to-interference ratio at each end device. However, the benefit of the capture effect cannot be realized simultaneously in all end devices owing to its characteristics. To avoid performance degradation of the specific end devices that are unable to realize the benefit of the capture effect, we propose transmit power allocation schemes. In the proposed technique, two types of allocated transmit power, which are designed in conjunction with each other, are used alternately in time. Numerical examples validate the effectiveness of the proposed technique.

Energy Efficiency Analysis in Modified GoF Spectrum Sensing-Based AF Relay Cooperative Cognitive Sensor Network with Energy Harvesting

In this paper, we propose a joint sensing duration and transmission power allocation scheme to maximize the energy efficiency (EE) of the secondary user (SU) in a cooperative cognitive sensor network (CSN). At the initial time slot of the frame, the secondary transmitter (ST) performs energy harvesting (EH) and spectrum sensing simultaneously using power splitting (PS) protocol. The modified goodness of fit (GoF) spectrum sensing algorithm is employed to detect the licensed spectrum, which is not sensitive to an inaccurate noise power estimate. Based on the imperfect sensing results, the ST will act as an amplify-and-forward (AF) relay and assist in transmission of the primary user (PU) or transmit its own data. The SU’s EE maximization problem is constructed under the constraints of meeting energy causality, sensing reliability, and PU’s quality of service (QoS) requirement. Since the SU’s EE function is a nonconvex problem and difficult to solve, we transform the original problem into a tractable convex one with the aid of Dinkelbach’s method and convex optimization technique by applying a nonlinear fractional programming. The closed-form expression of the ST’s transmission power is also derived through Karush-Kuhn-Tucker (KKT) and gradient method. Simulation results show that our scheme is superior to the existing schemes.

MIMO Full-Duplex Networks With Limited Knowledge of the Relay State

Full-duplex (FD)-enabled relay networks represent a relevant solution to two critical needs of next-generation networks, namely, radio coverage extension and high spectral efficiency of wireless communications. Under practical conditions, however, the FD mode may not be the best operational setting for the relay; rather, operating in half-duplex may be more convenient when harsh channel conditions add up to self-interference. One of the fundamental challenges in the design of FD relay networks is thus how to determine the relay operational mode and the value of transmit power at both the relay and the data source, so that the achievable data rate is maximized as time varies. We address this problem in a two-hop, MIMO network, accounting for practical operational conditions in which the source is unaware of the symbols that the relay is transmitting. In light of the problem complexity, we also derive a lower-bound to the maximum achievable rate, which proves to be tight, especially for low-medium SNR values. We then tackle massive MIMO networks, and exploit our asymptotic analysis in the number of antennas to derive a low-complexity, yet highly efficient, operational mode and transmit power allocation scheme for a finite-size scenario.

QoE-Driven UAV-Enabled Pseudo-Analog Wireless Video Broadcast: A Joint Optimization of Power and Trajectory

The explosive demands for high quality mobile video services have caused heavy overload to the existing cellular networks. Although the small cell has been proposed to alleviate such a problem, the network operators may not be interested in deploying numerous base stations (BSs) due to expensive infrastructure construction and maintenance. The unmanned aerial vehicles (UAVs) can provide the low-cost and quick deployment, which can support high-quality line-of-sight communications and have become promising mobile BSs. In this paper, we propose a quality-of-experience (QoE)-driven UAV-enabled pseudo-analog wireless video broadcast scheme, which provides mobile video broadcast services for ground users (GUs). Due to limited energy available in UAV, the aim of the proposed scheme is to maximize the minimum peak signal-to-noise ratio (PSNR) of GUs’ video reconstruction quality by jointly optimizing the transmission power allocation strategy and the UAV trajectory. Firstly, the reconstructed video quality at GUs is defined under the constraints of the UAV's total energy and motion mechanism, and the proposed scheme is formulated as a complex non-convex optimization problem. Then, the optimization problem is simplified to obtain a tractable suboptimal solution with the help of the block coordinate descent model and the successive convex approximation model. Finally, the experimental results are presented to show the effectiveness of the proposed scheme. Specifically, the proposed scheme can achieve over 1.6 dB PSNR gains in terms of GUs’ minimum PSNR, compared with the state-of-the-art schemes, e.g., DVB, SoftCast, and SharpCast.

Joint resource block and power allocation through distributed learning for energy efficient underlay D2D communication with rate guarantee

In this paper, we propose a novel distributed energy efficient joint resource block (RB) and discrete transmit power allocation scheme for an underlay device-to-device (D2D) network. In addition to minimizing the total transmit power of the D2D tier, the proposed scheme also ensures the rate constraints for all the cellular user equipments (CUEs) and D2D pairs. D2D pairs learn the RB and transmit power to be used by playing a game in Satisfaction Form (SF). The Efficient Satisfaction Equilibrium (ESE) of the game is shown to be the RB and discrete transmit power allocation with the lowest aggregate transmit power, in the case when the rate requirements of all the D2D pairs can be satisfied with non-zero transmit powers; else, the game is shown to converge to the K-Person Satisfaction Point (K-PSP), where the largest subset of D2D pairs are satisfied. The base station (BS) then decides to reject or accommodate the D2D pairs to ensure the rate constraints of the CUEs. The proposed scheme is established to be equivalent to the deferred acceptance (DA) algorithm applied to a many-to-one matching game. We exploit this equivalence to investigate the stability and optimality of the solution. The performance of the proposed scheme is evaluated and compared with existing schemes in the literature.

Energy-Efficient Computation Offloading and Transmit Power Allocation Scheme for Mobile Edge Computing

Mobile edge computing (MEC) is considered a promising technique that prolongs battery life and enhances the computation capacity of mobile devices (MDs) by offloading computation-intensive tasks to the resource-rich cloud located at the edges of mobile networks. In this study, the problem of energy-efficient computation offloading with guaranteed performance in multiuser MEC systems was investigated. Given that MDs typically seek lower energy consumption and improve the performance of computing tasks, we provide an energy-efficient computation offloading and transmit power allocation scheme that reduces energy consumption and completion time. We formulate the energy efficiency cost minimization problem, which satisfies the completion time deadline constraint of MDs in an MEC system. In addition, the corresponding Karush–Kuhn–Tucker conditions are applied to solve the optimization problem, and a new algorithm comprising the computation offloading policy and transmission power allocation is presented. Numerical results demonstrate that our proposed scheme, with the optimal computation offloading policy and adapted transmission power for MDs, outperforms local computing and full offloading methods in terms of energy consumption and completion delay. Consequently, our proposed system could help overcome the restrictions on computation resources and battery life of mobile devices to meet the requirements of new applications.

Generalized Coordinated Multipoint (GCoMP)-Enabled NOMA: Outage, Capacity, and Power Allocation

A novel generalized coordinated multi-point transmission (GCoMP)-enabled non-orthogonal multiple access (NOMA) scheme is proposed. In particular, distributed base stations (BSs) in a network coverage area cooperate on the downlink to serve a set of user equipments (UEs) using the same transmission frequency band. Furthermore, all UEs associated to a BS and using a particular frequency band forms a single NOMA cluster. The number of BSs serving a UE in a particular frequency band is referred to as the order of clustering (or order of BS cooperation). To evaluate the proposed scheme, we derive a closed-form expression for the probability of outage for a UE with different orders of BS cooperation. To obtain important insights on the performance of the proposed system, approximate (asymptotic) expressions for the probability of outage and outage capacity are derived considering both perfect and imperfect channel state information (CSI) estimation. We observe that improved spectral efficiency with a large number of UEs per NOMA cluster can be achieved by increasing the clustering order (i.e., number of cooperating BSs per UE). Furthermore, an optimal transmission power allocation scheme that jointly allocates transmission power fractions from all cooperating BSs to all connected UEs is developed.

Interval type-2 fuzzy logic based transmission power allocation strategy for lifetime maximization of WSNs

In wireless sensor networks (WSNs), it is critical to design an advisable transmission power allocation strategy for balancing the latency and energy efficiency, and prolonging the lifetime of WSNs. However, some measured key parameters, e.g., data latency, energy consumption and communication radius, are with high levels of uncertainties, which deteriorate the transmission power allocation performance greatly. How to employ an advanced method to deal with the uncertainties and to further improve the network performance is a pressing issue. Type-2 fuzzy logic system (T2FLS) as a powerful tool for handling the uncertainties provides an effective way for designing such advisable allocation strategies. Therefore, this paper adopts the interval T2FLS (IT2FLS) to design the transmission power allocation (TPA) strategy for lifetime maximization of WSNs. Firstly, the problem of lifetime enhancement in WSNs is formulated in detail, and then it is converted into a TPA problem. Secondly, the IT2FLS method is applied to the transmission power decision making process for maximizing the lifetime of WSNs. In the designed IT2FLS-based TPA strategy, expected latency, residual energy and distance between nodes are taken as input variables, while the transmission power and communication radius are considered as the output variables. Finally, both simulation and experiment results are given. The results indicate that the proposed TPA strategy using IT2FLS can effectively realize the tradeoff between the latency and energy efficiency, and can prolong the network lifetime of the WSNs. Moreover, compared with other TPA strategies, including the minimum total energy algorithm, the flow augmentation algorithm and the type-1 fuzzy logic method, the proposed IT2FLS-based TPA strategy has obvious advantages in terms of network lifetime, average latency and energy consumption.

Joint Interleaver and Modulation Design For Multi-User SWIPT-NOMA

Radio frequency (RF) signals can be relied upon for conventional wireless information transfer (WIT) and for challenging wireless power transfer (WPT), which triggers the significant research interest in the topic of simultaneous wireless information and power transfer (SWIPT). By further exploiting the advanced non-orthogonal-multiple-access (NOMA) technique, we are capable of improving the spectrum efficiency of the resource-limited SWIPT system. In our SWIPT system, a hybrid access point (H-AP) superimposes the modulated symbols destined to multiple WIT users by exploiting the power-domain NOMA, while WPT users are capable of harvesting the energy carried by the superposition symbols. In order to maximise the amount of energy transferred to the WPT users, we propose a joint design of the energy interleaver and the constellation rotation based modulator in the symbol-block level by constructively superimposing the symbols destined to the WIT users in the power domain. Furthermore, a transmit power allocation scheme is proposed to guarantee the symbol-error-ratio (SER) of all the WIT users. By considering the sensitivity of practical energy harvesters, the simulation results demonstrate that our scheme is capable of substantially increasing the WPT performance without any remarkable degradation of the WIT performance.

Dual-Band Fading Multiple Access Relay Channels

Relay cooperation and integrated microwave and millimeter-wave (mm-wave) dual-band communication are likely to play key roles in 5G. In this paper, we study a two-user uplink scenario in such dual-bands, modeled as a multiple-access relay channel (MARC), where two sources communicate to a destination assisted by a relay. However, unlike the microwave band, transmitters in the mm-wave band must employ highly directional antenna arrays to combat the ill effects of severe path-loss and small wavelength. The resulting mm-wave links are point-to-point and highly directional, and thus used to complement the microwave band by transmitting to a specific receiver. For such MARCs, the capacity is partially characterized for sources that are near the relay in a joint sense over both bands. We then study the impact of the mm-wave spectrum on the performance of such MARCs by characterizing the transmit power allocation scheme for phase faded mm-wave links that maximizes the sum-rate under a total power budget. The resulting scheme adapts the link transmission powers to channel conditions by transmitting in different modes , and all such modes and corresponding conditions are characterized. Finally, we study the properties of the optimal link powers and derive practical insights.

Fusion Rules for Distributed Detection in Clustered Wireless Sensor Networks With Imperfect Channels

In this paper, we investigate fusion rules for distributed detection in large random clustered wireless sensor networks with a three-tier hierarchy; the sensor nodes (SNs), the cluster heads (CHs), and the fusion center (FC). The CHs collect the SNs’ local decisions and relay them to the FC, which then fuses them to reach the ultimate decision. The SN–CH and the CH–FC channels suffer from additive white Gaussian noise. In this context, we derive the optimal log-likelihood ratio (LLR) fusion rule, which turns out to be intractable. So, we develop a sub-optimal linear fusion rule (LFR) that weighs the cluster's data according to both its local detection performance and the quality of the communication channels. In order to implement it, we propose an approximate maximum likelihood based LFR (LFR-aML), which estimates the required parameters for the LFR. We also derive Gaussian-tail upper bounds for the detection and false alarms probabilities for the LFR. Furthermore, an optimal CH transmission power allocation strategy is developed by solving the Karush–Kuhn–Tucker conditions for the related optimization problem. Extensive simulations show that the LFR attains a detection performance near to that of the optimal LLR and confirms the validity of the proposed upper bounds. Moreover, when compared to equal power allocation, simulations show that our proposed power allocation strategy achieves a significant power saving at the expense of a small reduction in the detection performance.

Adaptive feedback bits and power allocation for dynamic TDD systems

In next-generation wireless communication systems, a dynamic time division duplex (TDD) system is promising to support simultaneous uplink (UL) and downlink (DL) transmissions. We herein consider a fixed number of feedback bits per DL user, where each DL user reports its quantized channel direction information (CDI) of the interference channel to a serving DL base station via its dedicated feedback channel. Based on the quantized CDI feedback, we design the UL and DL transmit zero-forcing beamforming (ZFBF) to mitigate the interference signals caused by the coexistence of the UL and DL transmissions. To maximize the DL data rate, the challenge of interference cancellation lies in how many feedback bits are adaptively allocated for the transmission of the quantized CDI of each channel link. This paper proposes an adaptive feedback bits allocation scheme which minimizes the mean rate loss between perfect channel knowledge and limited feedback system. We also propose the UL transmit power allocation scheme under the interference power constraint from the UL user to the DL user when the number of feedback bits for the quantized CDI is given. To jointly solve the feedback bits allocation and the UL transmit power allocation problems, we use an iterative scheme to maximize the DL data rate while satisfying the constraint of interference power. Finally, we investigate how many feedback bits per DL user are required to maintain a constant mean rate loss. The simulation results show that the proposed adaptive feedback bits allocation scheme significantly increases the DL data rate compared with the conventional schemes.

Energy-Aware Mobile Edge Computation Offloading for IoT Over Heterogenous Networks

The rapid development of the Internet of Things gives rise to the emergence of delay-sensitive and computation-intensive applications. Due to the inherent long delay of cloud computing and the limited resources at end devices, mobile edge computing is considered a promising approach to meet the stringent delay requirement of such demanding applications. To handle the massive connection of the Internet of Things, the 5G network is shifting toward heterogenous architecture, where each end device can access more than one edge server (e.g., base stations and access points). In the presence of multiple edge servers, this paper investigates the interesting problem of how to exploit the heterogenous computation resources at the network edge to achieve the best energy efficiency among multiple end devices while satisfying their delay requirements. We study a computation offloading management problem by jointly considering the heterogeneous computation resources, latency requirements, power consumption at end devices, and channel states. The formulated energy minimization problem falls into the category of mixed-integer and nonlinear program. To solve it efficiently, we decompose the original problem into two subproblems and propose an iterative solution framework to solve for transmission power allocation strategy and computation offloading scheme. Through simulation results, we show that the proposed solution is competitive when compared with the optimal solution. Moreover, we leverage the optimal solutions to analyze the impact of computation resource distribution on energy consumption and computation offloading decision.

Scalable Virtualization and Offloading-Based Software-Defined Architecture for Heterogeneous Statistical QoS Provisioning Over 5G Multimedia Mobile Wireless Networks

As a crucial step moving towards the next generation of super-fast wireless networks, recently the fifth-generation (5G) mobile wireless networks have received a plethora of research attention and efforts from both the academia and industry. The 5G mobile wireless networks are expected to provision distinct delay-bounded quality of service (QoS) guarantees for a wide range of multimedia services, applications, and users with extremely diverse requirements. However, how to efficiently support multimedia services over 5G wireless networks has imposed many new challenging issues not encountered before in the fourth-generation wireless networks. To overcome these new challenges, we propose a novel network-function virtualization and mobile-traffic offloading based software-defined network (SDN) architecture for heterogeneous statistical QoS provisioning over 5G multimedia mobile wireless networks. Specifically, we develop the novel SDN architecture to scalably virtualize wireless resources and physical infrastructures, based on user’s locations and requests, into three types of virtual wireless networks: virtual networks without offloading, virtual networks with WiFi offloading, and virtual networks with device-to-device offloading. We derive the optimal transmit power allocation schemes to maximize the aggregate effective capacity, overall spectrum efficiency, and other related performances for these three types of virtual wireless networks. We also derive the scalability improvements of our proposed three integrated virtual networks. Finally, we validate and evaluate our developed schemes through numerical analyses, showing significant performance improvements as compared with other existing schemes.