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Recently, model-free power control approaches have been developed to achieve the near-optimal performance of cell-free (CF) massive multiple-input multiple-output (MIMO) with affordable computational complexity. In particular, deep reinforcement learning (DRL) is one of such promising techniques for realizing effective power control. In this paper, we propose a model-free method adopting the deep deterministic policy gradient algorithm (DDPG) with feedforward neural networks (NNs) to solve the downlink max-min power control problem in CF massive MIMO systems. Our result shows that compared with the conventional convex optimization algorithm, the proposed DDPG method can effectively strike a performance-complexity trade-off obtaining 1,000 times faster implementation speed and approximately the same achievable user rate as the optimal solution produced by conventional numerical convex optimization solvers, thereby offering effective power control implementations for large-scale systems. Finally, we extend the DDPG algorithm to both the max-sum and the max-product power control problems, while achieving better performance than that achieved by the conventional deep learning algorithm. [ABSTRACT FROM AUTHOR]

Power control is becoming increasingly essential for the fifth-generation (5G) and beyond systems. An example use-case, among others, is the unmanned-aerial-vehicle (UAV) communications where the nearly line-of-sight (LoS) radio channels may result in very low signal-to-interference-plus-noise ratios (SINRs). The authors in (Chiang et al., 2007) proposed to efficiently and reliably solve this kind of non-convex problem via a series of geometrical programmings (GPs) using condensation approximation. However, it is only applicable for a small-scale network with several communication pairs and practically infeasible with more (e.g., tens of) nodes to be jointly optimized. We therefore in this paper aim to provide new insights into this problem. By properly introducing auxiliary variables, the problem is transformed to an equivalent form which is simpler and more intuitive for condensation. A novel condensation method with linear complexity is also proposed based on the form. The enhancements make the GP-based power control feasible for both small- and especially large-scale networks that are common in 5G and beyond. The algorithm is verified via simulations. A preliminary case study of uplink UAV communications also shows the potential of the algorithm. [ABSTRACT FROM AUTHOR]

This paper investigates the benefits of incorporating full-duplex (FD) into an underlaid device-to-device (D2D) cellular network via centralized and distributed power control mechanisms. In the considered system, D2D users operate in an FD mode under the adverse effect of realistic residual self-interference, and their locations are modeled by a homogeneous spatial Poisson point process. By first considering a centralized power control scheme, we first formulate an optimization problem that maximizes the D2D link sum-rate under the constraint on minimum target signal-to-interference-plus-noise ratio (SINR) at each user. Since the problem is nonconvex, we propose a difference of convex based method to transform the problem into a sequence of convex subproblems which can be solved efficiently. The obtained solutions help to calculate the coverage probability of both cellular and D2D links, showing that a very high coverage probability of cellular link can be achieved while successfully supporting a large number of active D2D links. In the second part of the paper, we consider a distributed power control scheme where only the local channel state information of direct link between respective D2D users is needed. By utilizing the tools of stochastic geometry, we derive closed-form approximations of coverage probabilities for both cellular and D2D links. Specifically, we apply Laplace transforms and novel approximations that accurately approximate the expected values of fractional and exponential functions of random variables to obtain the distribution functions of SINRs at the base-station and D2D users in a closed form. By further taking the average over the distributions of cellular and D2D link distances, we then arrive at the closed-form approximations of cellular and D2D coverage probabilities. In addition, based on the approximation of D2D link coverage probability, an analytical expression for the D2D link sum-rate is also obtained, and it can be effectively calculated. [ABSTRACT FROM AUTHOR]

This paper raises the question of whether the secondary user can attain a nonzero achievable rate without causing capacity loss at the primary user, even when it is utilizing the channel in cognitive radio networks (CRNs). It is assumed that secondary nodes are aware of the channel state information (CSI) of primary nodes and of how the primary nodes operate, whereas the primary nodes operate with no prior knowledge about the secondary nodes. We first propose a full-duplex relaying protocol for the cognitive radio (CR) network with a single relay node shared by both the primary and the secondary networks. In this case, the shared relay is assumed to have full CSI of the primary nodes and to know how the primary and secondary nodes operate. The proposed relaying protocol enables the secondary network to achieve nonzero rates without causing capacity loss at the primary network in a certain channel condition. Then, we also propose three half-duplex relaying protocols for the CR network with two relays, each of which is dedicated to the primary or the secondary network, respectively. It is shown that appropriate combinations of the proposed three half-duplex relaying protocols make it always possible for the secondary network to achieve nonzero rates without causing capacity loss at the primary network. Achievable rates of the proposed full- and half-duplex relaying protocols are evaluated through extensive computer simulations. Simulation results show that the proposed relaying protocols provide nonzero achievable rates of the secondary network over a wide range of signal-to-noise ratios (SNRs). [ABSTRACT FROM PUBLISHER]

In this paper, we study the problem of utility maximization in the uplink of vehicle-to-infrastructure communication systems. The studied scenarios consider four practical aspects of mobile radio communication links: i) Interference between adjacent channels, ii) interference between roadside units along the way, iii) fast and slow channel fadings, and iv) Doppler shift effects. We present first the system model for the IEEE 802.11p standard, which considers a communication network between vehicles and roadside infrastructure. Next, we formulate the problem of utility maximization in the network, and propose a distributed optimization scheme. This distributed scheme is based on a two-loop feedback configuration, where an outer-loop establishes the optimal signal to interference-noise ratio (SINR) that maximizes the utility function per vehicle and defines a quality-of-service objective. Meanwhile, inner-control loops adjust the transmission power to achieve this optimal SINR reference in each vehicle node regardless of interference, time-varying channel profiles and network latency. The computation complexity of the distributed utility maximization scheme is analyzed for each feedback loop. Simulation results indicate that the proposed scheme reaches the objective SINRs that maximize utility and improve energy efficiency in the network with a low time cost. The results also show that the maximum utility is consistently achieved for different propagation scenarios inside the vehicular communication network. [ABSTRACT FROM AUTHOR]

Interference is one of the most critical issues in the device-to-device (D2D)-enabled heterogeneous cellular networks (HetCNets) due to the coexistence of D2D pairs and various types of cellular user equipments (UEs) that operate in the same spectrum. In this paper, an interference management scheme of joint mode selection and power control is proposed to solve the issue in D2D-enabled HetCNets. In the scheme, we present power control with interference limited area (PC-ILA) in which power control is utilized to adjust the ILA dynamically. Furthermore, according to different ILA, users can select different communication modes to solve the problem of spectrum resource waste caused by a single communication mode. Numerical simulation results are provided to demonstrate the feasibility of the proposed scheme and its superiority over other schemes. Moreover, the proposed mode selection method achieves superior performance compared with existing well-known methods. [ABSTRACT FROM AUTHOR]

In the heterogeneous networks (HetNets), the downlink-uplink decoupled (DUDE) user association is a very promising technology that can employ different association strategies for uplink and downlink. The DUDE mode has great potential for improving system capacity and frequency efficiency. However, interference between the DUDE user equipment (DUDE UE), macro user equipment (MUE) and small user equipment (SUE) still needs to be considered and properly tackled. Therefore, this paper presents an optimization scheme of frequency allocation and power control to improve the communication quality of users. Firstly, the multiple region frequency allocation (MRFA) scheme is proposed for non-uniform user distribution to alleviate interference among users and allocate spectrum resources equally to dense users. This scheme is modelled as a sub-region partition problem with maximum sum rate, which can disperse densely distributed users to different sub-bands for transmission. Secondly, the convergent power control (CPC) algorithm is considered to improve the transmission performance of each user. It can converge the transmit power to the optimal transmit power for reducing interference among co-channel users when there is no disturbance in the network. The CPC algorithm can also make the signal-to-interference-plus-noise-ratio (SINR) of each active user always greater than the target threshold until the end of communication by dynamically adjusting the transmit power of users. Simulation results show that the joint scheme of MRFA and CPC achieves a higher system throughput and better user performance than existing frequency allocation schemes or power control schemes. [ABSTRACT FROM AUTHOR]

In this paper, distributed joint power and frequency allocation problem is studied. First, we present a distributed power update algorithm for the general wireless networks that eliminates the feasibility issue encountered in the well-known Foschini-Miljanic algorithm. Then, the proposed algorithm is extended by considering Orthogonal Frequency Division Multiple Access (OFDMA) femtocell networks in which each femto base station has more than one user. In addition, a frequency allocation scheme is developed in order to increase the maximum achievable signal-to-interference-plus-noise ratio (SINR). Subsequently, we present a joint frequency/power update algorithm by combining the proposed frequency allocation scheme with the power update algorithm. Convergence and optimality analyses of all the proposed algorithms are carried out and the theoretical results are illustrated with numerical results. [ABSTRACT FROM AUTHOR]

In this paper, we evaluate the uplink bit error rate (BER) of multicarrier-code-division-multiple-access (MC-CDMA) cellular systems with multiuser-maximum-likelihood detector (MU-MLD). The scenario considers perfect power control, own-cell interference (or multiple access interference—MAI), interference from co-cells (or co-cell interference—CCI), additive white Gaussian noise, exponential path-loss and slow frequency-selective Rayleigh fading. Upper bound expressions to evaluate the mean BER are obtained, which are functions of the signal-to-noise ratio (SNR), the number of users, the spreading factor, and the channel reuse factor. For BPSK and 4-QAM (quadrature amplitude modulation), closed-form expressions involving the analytical calculation of pairwise error probabilities are obtained. For 16-QAM and 64-QAM, we show that the number of pairwise error probabilities needed to obtain the BER can be simplified through the constellations symmetry. The procedure for obtaining this simplification is detailed. Also, by considering BER asymptotes, expressions for the SNR penalty due to MAI are derived. Monte Carlo simulations verify the analytical expressions accuracy. In the simulations, the MU-MLD is implemented through the sphere decoder algorithm with MMSE QR factorization. Results show that MC-CDMA does not lose diversity due to MAI. Moreover, CCI significantly affects the system performance. As a consequence, it produces floors in the BER curves. [ABSTRACT FROM PUBLISHER]

This paper introduces a fair and energy-efficient resource allocation framework in spectrum-sharing wireless networks with quality-of-service guarantees. Consider the tradeoff between energy efficiency and spectral efficiency, the multiobjective problem of spectral efficiency and energy efficiency is transformed into a problem that minimizes the total power consumption and maximizes the achievable utility, subject to power constraints and rate outage probability constraints. We then analyze the complexity of the considered problem; particularly, the optimization problem is NP-Hard when $0 < \alpha < 1$ and $\alpha =0$ and is convex for other values of the fairness index $\alpha$. After that, we adopt the successive convex approximation (SCA) approach to approximate and transform the NP-hard nonconvex optimization problem into a sequence of convex programs and propose two iterative SCA-based resource allocation algorithms. Extensive simulation results are presented to demonstrate the effectiveness and outperformance of the proposed algorithms over existing frameworks. [ABSTRACT FROM PUBLISHER]

This paper considers the shortest link scheduling problem in wireless networks under the signal-to-interference-plus-noise ratio (SINR) model. We propose an $O({}\log({}l_{\max}/l_{\min}{}){})-approximation algorithm called shortest link scheduling with power control (SLSPC) with oblivious power assignment and an O(\log1+\varphi(l\max/l\min)-approximation algorithm called shortest link scheduling with uniform or mean power assignment (SLSUM) with uniform or mean power control, where \varphi > 0 is a constant serving as a regulatory factor for slight transmit power adjustment, and where l\max and l\min denote the lengths of the longest and shortest links, respectively. We conduct a rigorous theoretical performance analysis to analyze the feasibility and approximation factors of the proposed algorithms. We also carry out an extensive comparison-based simulation study, whose results indicate that the performances of SLSPC and SLSUM are superior over the state of the art as the set of the so-called “black and gray” links, which are difficult to schedule and should be sequentially scheduled, is completely removed by adjusting the transmit power appropriately via $\varphi$. Our numerical analysis demonstrates that the approximation ratios of our algorithms are tighter than the best known ratios. [ABSTRACT FROM PUBLISHER]

In two-tier femtocell networks, adjusting the transmission power values of femtocell base stations (BSs) such that indoor users receive high signal quality while limiting leakage to outdoor users is an important problem. This paper proposes a novel distributed and self-optimized power adjustment algorithm for two-tier femtocell networks, in which a BS adjusts the transmission power based on the signal quality of neighboring BSs. Achieving fairness among users with minimal information exchange is desired. There are no predefined target parameters used to adjust transmission power, contrary to existing approaches in the literature. The convergence properties of the algorithm under fixed and time-varying communication infrastructures are investigated. The performance is further verified by simulations and comparisons with other algorithms for the coverage problem. [ABSTRACT FROM PUBLISHER]

Cooperative spectrum sensing may cause a high sensing overhead to secondary users (SUs) and induce much interference to primary users (PUs) due to detection result reporting, although it can improve the detection probability. In this paper, we propose two novel selective-reporting-based cooperative spectrum sensing strategies, called random-selection reporting (RSR) and best-selection reporting (BSR), aimed at reducing the sensing overhead of SUs and limiting the induced interference to PUs. By considering the interference impact on decision reporting from PUs, we derive closed-form expressions of false-alarm probability and detection probability over Rayleigh fading channels for traditional, RSR, and BSR strategies, respectively. We also analyze the interference impact on PUs from cooperative SUs and then show that such interference can be limited by power control to satisfy a given quality-of-service (QoS) requirement of primary transmissions. Finally, numerical and simulation results reveal that the proposed strategies can remarkably reduce the sensing overhead without degrading the detection performance compared with the traditional case. Moreover, we show that both RSR and BSR can achieve minimized miss detection probability and sensing overhead by adjusting the sensing time allocation. [ABSTRACT FROM PUBLISHER]

How to associate a femto user (FU) to an appropriate femto base station (FBS) to avoid interference and maximize the achievable data rate (ADR) of FUs has attracted a lot of attention in femtocell networks. The evidence provided in this paper proves it to be an NP-complete problem. To maximize the ADR of the FUs, the methods for assigning FUs to neighboring FBSs are examined to determine the required transmit power level (TPL) adjustments for the FBSs to mitigate the downlink (DL) interference among the FBSs and the macro base station (MBS). Traditionally, the linear programming (LP) approach is adopted to obtain the optimal solution for this problem. However, the LP approach requires substantially more time to obtain the solution. To lessen this drawback, we propose an easy but smarter scheme, i.e., the smart FBS selection algorithm (SFSA), to distribute FUs to the noninterfered FBSs and to obtain the maximal ADR for each FU. If the SFSA fails to solve this problem, a DL power-control algorithm (DPCA) is employed to find a solution that causes the least amount of interference. The simulation results show that the SFSA and DPCA require only a minor amount of computation time to obtain a feasible solution. The results show that the maximal data rates of the FUs obtained using the SFSA and DPCA are comparable to that of the LP approach. [ABSTRACT FROM PUBLISHER]

We consider the joint subchannel allocation and power control problem for orthogonal frequency-division multiple-access (OFDMA) femtocell networks in this paper. Specifically, we are interested in the fair resource-sharing solution for users in each femtocell that maximizes the total minimum spectral efficiency of all femtocells subject to protection constraints for the prioritized macro users. Toward this end, we present the mathematical formulation for the uplink resource-allocation problem and propose an optimal exhaustive search algorithm. Given the exponential complexity of the optimal algorithm, we develop a distributed and low-complexity algorithm to find an efficient solution for the problem. We prove that the proposed algorithm converges and we analyze its complexity. Then, we extend the proposed algorithm in three different directions, namely, downlink context, resource allocation with rate adaption for femto users, and consideration of a hybrid access strategy where some macro users are allowed to connect with nearby femto base stations (FBSs) to improve the performance of the femto tier. Finally, numerical results are presented to demonstrate the desirable performance of the proposed algorithms. [ABSTRACT FROM PUBLISHER]

In wireless networks for spectrum sharing among heterogeneous nodes, an issue of significant interest is the interference among coexisting systems, and understanding the essential quantities, such as interference distribution, is fundamental to the design of spatial spectrum sharing methods. This paper analyzes the performance of heterogeneously characterized nodes and investigates efficient spectrum sharing methods for single-input–multiple-output (SIMO) networks where nodes with different capabilities and requirements are spatially distributed according to homogeneous Poisson point processes (PPPs). Transmit power control strategies, such as fixed transmit power control and distance-based transmit power control, are applied, and it is demonstrated that their effects on the system performances depend on the multiple-antenna receiving methods. Furthermore, the underlay and overlay methods are considered for use as spectrum sharing methods. In addition, it is demonstrated that careful resource balancing among heterogeneous nodes contributes to minimizing the total amount of wireless resources required to meet the target outage constraints for all nodes, and the two spectrum sharing methods have the same performance in heterogeneous SIMO networks with low node densities. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a universal joint base station (BS) association (BSA) and power control (PC) algorithm for heterogeneous cellular networks. Specifically, the proposed algorithm iteratively updates the BSA solution and the transmit power of each user. Here, the new transmit power level is expressed as a function of the power in the previous iteration, and this function is called the power update function (puf). We prove the convergence of this algorithm when the puf of the PC strategy satisfies the so-called “two-sided scalable (2.s.s.) function” property. Then, we develop a novel hybrid PC (HPC) scheme by using noncooperative game theory and prove that its corresponding puf is 2.s.s. Therefore, this HPC scheme can be employed in the proposed joint BSA and PC algorithm. We then devise an adaptation mechanism for the HPC algorithm so that it can support the signal-tointerference-plus-noise ratio (SINR) requirements of all users whenever possible while exploiting multiuser diversity to improve the system throughput. We show that the proposed HPC adaptation algorithm outperforms the well-known Foschini–Miljianic PC algorithm in both feasible and infeasible systems. In addition, we present the application of the developed framework to design a hybrid access scheme for two-tier macrocell–femtocell networks. Numerical results are then presented to illustrate the convergence of the proposed algorithms and their superior performance, compared with existing algorithms in the literature. [ABSTRACT FROM PUBLISHER]

This paper introduces the novel concepts for decentralized relay-selection schemes based on the coalitional game theory that establishes the dynamic formation of coalitions in a wireless relay network. We present an efficient power-allocation protocol for wireless data transmission among coalitions based on a noncooperative power control game. Through this theoretical framework, source nodes are able to form stable coalitions and set their transmission power in a completely distributed fashion. Numerical results show that the proposed algorithm achieves a significant reduction in power consumption and an improvement in payoff for the transmitter nodes when compared with the noncooperative power control game with pricing (NPGP). We investigate the optimality of such joint relay-selection and power-allocation problems to affirm the performance of the proposed scheme. We propose an iterative joint relay-selection and power-allocation algorithm with a low degree of complexity and show that the distributed scheme achieves a comparable performance with the centralized case. [ABSTRACT FROM PUBLISHER]

Based on the analysis of the feature of cognitive radio (CR) networks, we build a relevant interference model. Cognitive users should particularly consider the problem of interference with licensed users and satisfy the signal-to-interferenceplus-noise ratio (SINR) requirement at the same time. We propose a new iterative algorithm using the game theory in this paper. We consider not only the SINR requirement as other game algorithms but also the influence of power threshold. The variable power limit is the characteristic of CR. We prove the convergence of the algorithm and the existence of Nash equilibrium. According to different power thresholds, we give an approach for solving the problem of coexistence between licensed user and cognitive user in a cognitive system. The algorithm has the advantage that it can be distributively implemented, and the method converges relatively fast. Numerical results are presented to show that the proposed approach has better antinoise effect and capacity. [ABSTRACT FROM PUBLISHER]

In wireless communication systems with multiple users, the near–far effect and the cochannel interferences decrease the spectral efficiency and system performance. An efficient known method to combat these destructive effects is to properly adjust the transmit powers. A practical and efficient way for power control (PC) in cellular communication systems is the autonomous distributed PC (DPC). In this method, the transmit power of each link is independently modified based on the received signal-to-interference-plus-noise ratio (SINR) reported from the other side of that link. It is known that in a perfect scenario where the reported SINRs are exact, this algorithm converges to the optimum transmit powers. However, in the case of erroneous SINR reports, the transmit powers deviate from their optimum values. This paper addresses the destructive effect of inaccurate SINR reports on the performance of a DPC algorithm. Then, independent variable step-sizes that update the transmit powers are proposed, and convergence of the proposed DPC algorithm to the optimum solution of the original problem is analytically shown. Additionally, a protocol to adaptively tune the step-sizes in our algorithm, which improves the performance of PC in the presence of inaccurate SINR reports, is proposed. Computer simulations are used to study the performance of the proposed method in terms of both the speed of converges and the steady-state accuracy of link qualities. [ABSTRACT FROM PUBLISHER]