Opportunistic Power Control Research Articles

Distributed Opportunistic Power Control for Uplink Cell-Free Massive MIMO-IoT Networks Under Ricean Fading Channels

Distributed Opportunistic Power Control for Uplink Cell-Free Massive MIMO-IoT Networks Under Ricean Fading Channels

An Opportunistic Power Control Scheme for Mitigating User Location Tracking Attacks in Cellular Networks

Cellular networks have been successfully evolved over the decades. Especially, Long-Term Evolution (LTE) has been exceedingly successful and the security threats against LTE systems have increased rapidly. Particularly, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">tracking</i> LTE user devices has been shown to be effective as the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">temporary</i> user identifiers (IDs) are easily extracted and used to locate targeted devices by passive eavesdroppers. We notice that naive approaches, such as frequent updates of temporary user IDs, are <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">insufficient</i> to mitigate user-tracking attacks since the new and old temporary IDs for the same user device are easily <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">linkable</i> by adversaries who can measure the wireless channel characteristics between the user device and herself. In this paper, we propose an opportunistic uplink power control scheme to minimize the probability of successful user tracking by an adversary whose location is unknown. We devise the notion of average inference error probability in order to measure the level of users’ location privacy. Moreover, we derive the closed-form expression of the approximated average inference error probability and formulate an optimization problem to maximize the average inference error probability under a constraint of an allowable power budget for each user. Against a passive adversary, our proposed power control scheme effectively degrades an adversary’s inference ability by 50% when 10 users are scheduled in each transmission time slot, which will lead to almost 100% inference error at the adversary over multiple time slots.

Power Allocation in Cellular Networks Based on Outage Probability and Normalized SINR

In this paper, power allocation in cellular networks is proposed based on the outage probability and normalized signal to interference plus noise ratio (SINR). Upper and lower bounds on the outage probability are determined using the normalized SINR considering path loss, shadowing, and fading. The problems of minimizing the user power subject to outage probability and target SINR constraints are then considered as power allocation problems. These problems are solved using Perron-Frobenius theory and geometric programming (GP). The objectives are to efficiently provide users with flexible date rates and reduce the outage probability and user transmit power. Typically, only the path loss is considered in determining the outage probability whereas path loss, multipath fading and lognormal shadowing are considered in this paper along with the interference from other users. Results are presented which show that the proposed power allocation schemes provide better performance than the target SINR tracking power control (TPC), opportunistic power control (OPC), and temporary removal and feasibility check power control (DFC) algorithms.

Prioritised and selective power control in cellular wireless networks

Power control is used in cellular communications systems to reduce power consumption and satisfy as many users as possible by managing the mutual interference between users. In signal to interference plus noise ratio (SINR) tracking power control (TPC) schemes, all users are required to adjust their power levels for each iteration, which is inefficient. In this study, a prioritised and selective uplink power control scheme is proposed. Priority user requirements are satisfied first, and then as many normal users (NUs) as possible are satisfied with their target SINRs. In addition, if an NU is currently satisfied with its target SINR, it is not required to update its transmit power level. Conversely, NUs who are not satisfied update their power levels. Simulation results are presented, which show that the proposed scheme outperforms dynamic target SINR TPC and variable target SINR TPC in terms of power consumption and efficiency. In addition, the proposed scheme is better than target SINR TPC and opportunistic power control as the number of users increases.

Chance-constraint optimization of power control in cognitive radio networks

In this paper, to minimize the transmission power of cognitive users in underlay cognitive radio networks, a robust power control algorithm is proposed considering the uncertain channel gains. To deal with the uncertainty, we present an opportunistic power control strategy, i.e., the outage probability of all cognitive users and primary users should be reduced below their predefined thresholds. The strategy is the joint design of primary users’ communication protection and cognitive users’ optimal power allocation. A chance constraint robust optimization approach is applied, which can transform the uncertain problem into a deterministic problem. Then, a distributed probabilistic power algorithm is introduced, which ensures the optimization of cognitive users’ power allocation based on the standard interference function and restricts the interference at primary receivers by adjusting the maximum transmission power of cognitive users. Moreover, the admission control is introduced to exploit the network resources more effectively. Numerical results show the convergence and effectiveness of the proposed robust distributed power control algorithm.

Distributed power control for energy conservation in hybrid cellular network with Device-to-Device communication

Device-to-Device (D2D) communication has been proposed as a promising implementation of green communication to benefit the existed cellular network. In order to limit cross-tier interference while explore the gain of short-range communication, we devise a series of distributed power control (DPC) schemes for energy conservation (EC) and enhancement of radio resource utilization in the hybrid system. Firstly, a constrained opportunistic power control model is built up to take advantage of the interference avoidance methodology in the presence of service requirement and power constraint. Then, biasing scheme and admission control are added to evade ineffective power consumption and maintain the feasibility of the system. Upon feasibility, a non-cooperative game is further formulated to exploit the proft in EC with minor influence on spectral efficiency (SE). The convergence of the DPC schemes is validated and their performance is confrmed via simulation results.

Interference-Dependent Opportunistic Power Control for Multicarrier Interference Channels

We propose an interference-dependent and distributed algorithm for opportunistic power control (OPC) in interference channels for delay-tolerant data services with a view to maximizing each user's data rate while satisfying a given constraint on the total transmit power of all users. In doing so, we utilize a game-theoretic framework, in which the allocated power to each user on each subchannel depends on the subchannel's interference. In our scheme, each user's transmit power depends on transmit power levels of other users, which means that the game belongs to the so-called generalized Nash equilibrium (GNE) problems, which, in general, are hard to analyze. Nevertheless, we will show that the proposed game has at least one GNE and derive sufficient conditions for its uniqueness. Moreover, we derive sufficient conditions for the algorithm's convergence. Simulations confirm that our proposed scheme yields higher throughput for each user and/or has significantly improved energy efficiency.

Robust optimisation of power control for femtocell networks

In this study, the minimum transmission power of each femtocell user in a two-tier network, in which femtocells and macrocell use the spectrum simultaneously, is investigated. That is, the authors are aiming at finding the power that characterises robustness and energy-efficient when taking the uncertain gains into consideration. To solve the optimisation problem with uncertainty, an opportunistic power control strategy for the femtocells is introduced. Since the channel gain from a femtocell user to the femtocell base station is changeable with the environment, it is difficult to track channel gains instantaneously. For the reason that the mean channel gains, from the femtocell users to the femtocell base stations are usually achievable, the information of mean and probability density function are used to model the optimisation problem. Moreover, outage probability for each femtocell user's throughput is originated instead of considering the total throughput of the system, because high total throughput may not ensure that of each femtocell user. The signal-to-interference-plus-noise ratio of the macrocell is ensured by setting appreciate interference temperature. A distributed algorithm is designed to calculate the powers of femtocell users. Numerical results show the effectiveness of the proposed outage probabilistic method and the distributed algorithm.

On Opportunistic Power Control for Alamouti and SM MIMO Systems

Transmit antenna diversity and single user spatial multiplexing have become attractive in practical systems, because they achieve performance gains without requiring sophisticated channel state information (CSI) feedback mechanisms. On the other hand, when fast and accurate CSI at the transmitter is available, opportunistic power control (OPC) is an attractive alternative to signal-to-interference-and-noise ratio (SINR) target following approaches, because it maximizes throughput by taking advantage of fast channel variations. In this paper we examine the question whether OPC is worth the pain of obtaining fast CSI by evaluating the gains of OPC for the downlink of a system employing multiple input multiple output (MIMO) systems with Alamouti and open loop spatial multiplexing (SM). We formulate the OPC problem as a throughput maximization task subject to power budget and fairness constraints. We solve this task by the Augmented Lagrangian Penalty Function and find that without fairness constraints, OPC in concert with SM provides superior throughput. With increasingly tight fairness constraints, Alamouti along with equal power allocation becomes a viable alternative to the SM OPC scheme. Both from fairness and throughput perspectives, Alamouti along with OPC is particularly efficient when adaptive MCS is employed and users with large differences in channel qualities have to share the total transmit power.

Opportunistic power allocation strategies and fair subcarrier allocation in OFDM-based cognitive radio networks

In this paper we have studied the subcarrier and optimal power allocation strategy for OFDM-based cognitive radio (CR) networks. Firstly, in order to protect the primary user communication from the interference of the cognitive user transmissions in fading wireless channels, we design an opportunistic power control scheme to maximize the cognitive user capacity without degrading primary user's QoS. The mathematical optimization problem is formulated as maximizing the capacity of the secondary users under the interference constraint at the primary receiver and the Lagrange method is applied to obtain the optimal solution. Secondly, in order to limit the outage probability within primary user's tolerable range we analyze the outage probability of the primary user with respect to the interference power of the secondary user for imperfect CSI. Finally, in order to get the better tradeoff between fairness and system capacity in cognitive radio networks, we proposed an optimal algorithm of jointing subcarrier and power allocation scheme among multiple secondary users in OFDM-based cognitive radio networks. Simulation results demonstrate that our scheme can improve the capacity performance and efficiently guarantee the fairness of secondary users.

Opportunistic Power Control for Successive Interference Cancellation

This letter proposes an opportunistic power control for increasing the transmission rate of a secondary transmitter (ST) in frequency reused scenario. The environments considered herein have multiple primary transmitter/receiver pairs and one secondary transmitter/receiver pair using the same frequency band. In this scenario, we develop the opportunistic power control method for assisting successive interference cancellation (SIC) and optimal SIC order. Simulation results show that the proposed method improves the ST transmission rate significantly when compared to the method with no power control, and it exhibits a small throughput loss compared to the optimal technique while offering simpler implementation and using less transmission power.

Distributed Uplink Power Control with Soft Removal for Wireless Networks

In the well-known distributed target-SIR-tracking power control algorithm (TPC), when the system is infeasible (a constrained power vector does not exist to attain target-SIRs), all non-supported users (those who cannot obtain their target-SIRs) transmit at their maximum power. Such users inefficiently consume their energy, and cause interference to others, which increases the number of non-supported users. To deal with this, some non-supported users should decrease their transmit power (the gradual removal problem). We present a distributed power control scheme with gradual soft removal, by which either TPC or OPC (opportunistic power control) is used, depending on whether the ratio of interference-to-path-gain is below or above a threshold that is chosen by each user in a distributed manner. We show that our algorithm converges to a unique fixed-point in both feasible and infeasible systems, and that when the system is infeasible, it results in less outage with significantly less consumed power, as compared to TPC. We also provide a game theoretic analysis of our algorithm by introducing a new pricing when users are selfish. As our algorithm is fully distributed and requires only local information, it can be applied to both cellular and ad hoc networks. Simulation results confirm our analysis.

Convergence and Performance of Distributed Power Control Algorithms for Cooperative Relaying in Cellular Uplink Networks

We investigate an application of distributed power control (DPC) and opportunistic power control (OPC), respectively, to cooperative relaying systems that consist of multiple sources, multiple relays, and a single destination. Two types of relaying gains are considered for half-duplex amplify-and-forward (AF) relays: fixed and variable gains, respectively. Using half-duplex AF relays, remote users benefit by making the path loss smaller by two shorter paths. However, they lose bandwidth and suffer from additional interference due to amplification of the noise at the relays and the unnecessary signal from the relays, where power control plays an important role. We begin with redefining and extending the existing power control algorithms to be fit for the relaying environments and then, using standard techniques, construct the convergence, except when the number of variable-gain relays is even. With numerical investigation, we show the advantages and disadvantages of the power-controlled systems with relays in terms of the outage probability, the average transmit power consumption, and the transmission capacity. Simulation results show that DPC with relays achieves significant improvement in the outage performance and power consumption. On the other hand, in OPC, some negative effects arise by using the relays in the capacity since the relays increase the interference that severely affects the opportunistic capacity.

A Distributed Dynamic Target-SIR-Tracking Power Control Algorithm for Wireless Cellular Networks

The well-known fixed-target-signal-to-interference-ratio (SIR)-tracking power control (TPC) algorithm provides all users with their given feasible fixed target SIRs but cannot improve the system throughput, even if additional resources are available. The opportunistic power control (OPC) algorithm significantly improves the system throughput but cannot guarantee the minimum acceptable SIR for all users (unfairness). To optimize the system throughput subject to a given lower bound for the users' SIRs, we present a distributed dynamic target-SIR tracking power control algorithm (DTPC) for wireless cellular networks by using TPC and OPC in a selective manner. In the proposed DTPC, when the effective interference (the ratio of the received interference to the path gain) is less than a given threshold for a given user, that user opportunistically sets its target SIR (which is a decreasing function of the effective interference) to a value higher than its minimum acceptable target SIR; otherwise, it keeps its target SIR fixed at its minimum acceptable level. We show that the proposed algorithm converges to a unique fixed point starting from any initial transmit power level in both synchronous and asynchronous power-updating cases. We also show that our proposed algorithm not only guarantees the (feasible) minimum acceptable target SIRs for all users (in contrast to the OPC) but also significantly improves the system throughput, compared with the TPC. Furthermore, we demonstrate that DTPC, along with TPC and OPC, can be utilized to apply different priorities of transmission and service requirements among users. Finally, when users are selfish, we provide a game-theoretic analysis of our DTPC algorithm via a noncooperative power control game with a new pricing function.

Opportunistic distributed power control with adaptive QoS and fairness for wireless networks

AbstractThis paper presents a class of distributed power control algorithms for wireless networks which provides quality of service (QoS) fulfillment by exploiting the channel variability opportunistically. It is suitable for traffic sources requiring either a minimum or a prescribed QoS provision, and at the same time provides a fair resource allocation. Practical system constraints such as limitations on transmission power and modulation and coding schemes are considered in this framework. Moreover, it is analytically shown to be more energy efficient than the opportunistic power control. Two algorithms of this class are described and have their performance confronted with opportunistic algorithms. Copyright © 2009 John Wiley &amp; Sons, Ltd.

On cognitive radio networks with opportunistic power control strategies in fading channels

In this paper, we consider a cognitive radio system in fading wireless channels and propose an opportunistic power control strategy for the cognitive users, which serves as an alternative way to protect the primary user's transmission and to realize spectrum sharing between the primary user and the cognitive users. The key feature of the proposed strategy is that, via opportunistically adapting its transmit power, the cognitive user can maximize its achievable transmission rate without degrading the outage probability of the primary user. If compared with the existing cognitive protocols, which usually try to keep the instantaneous rate of the primary user unchanged, our strategy relieves the cognitive users from the burden of detecting and relaying the message of the primary user and relaxes the system synchronization requirements. The achievable rate of a cognitive user under the proposed power control strategy is analyzed and simulated, taking into account the impact of imperfect channel estimation. A modified power control strategy is also proposed to reduce the sensitivity of our strategy to the estimation errors. Its effectiveness is verified by the simulations.

An opportunistic power control algorithm for cellular network

We propose an opportunistic power control algorithm, which exploits channel fluctuation in order to maximize system throughput. The basic idea is that it instructs a transmitter to increase its power when the channel is good and to decrease its power when the channel is bad. The transmission rate is adjusted according to the received signal-to-interference ratio. The proposed algorithm is distributed and can be applied to systems in which the transmitters are connected to different receivers. We prove that the algorithm always converge to a unique fixed point and thus is stable. Simulation results show that a tremendous increase in system capacity can be achieved, when compared with other power control algorithms. Furthermore, the algorithm works well for nonreal-time terminals when other real-time terminals employ the target-tracking power control. It can also be extended to cases where maximum power constraint is imposed and soft handoff is executed.