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This paper addresses the problem of joint resource block (RB) and uplink transmission power allocation in a Device to Device (D2D) underlay cellular network via a game theoretic approach. In contrast to the majority of previous research works in this area, the proposed framework aims mainly at interference mitigation and energy efficiency. We do no...
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Citations
... The adaptive power control Q-learning algorithm is proposed to maximize system efficiency under optimal transmission power conditions, but Qlearning is flat, does not capture task structure well, and is particularly constrained by dimensional disasters [37]. To solve the optimization problem, a two-step distributed method is proposed in [38]. The RB allocation problem is expressed as a noncooperative game, and it is shown to be an accurate potential game. ...
Device-to-device (D2D) communication with direct terminal connection is a promising candidate for 5G communication, which increases the capacity of cellular networks and spectral efficiency. Introducing D2D communication to cellular users (CUs) will increase system capacity, and CUs will provide reusable channel resources for D2D users (DUs). However, the sharing of channel resources between CUs and DUs will lead to cofrequency interference and affect the communication quality of user terminals. As a means of improving spectrum utilization and solving cofrequency interference problems, a one-to-many D2D communication system model is established in cellular networks. Through model analysis, the interference between CUs and DUs is correlated with their distance from one another. Considering the different interference of CUs to DUs at different distances, an algorithm for resource allocation based on distance grouping is proposed. With this algorithm, DUs will reuse channel resources of CUs within a reasonable distance in the group, and interference between DUs and CUs will be minimized. The improved particle swarm optimization algorithm is used to solve the optimal power, to achieve the maximum transmission rate of the system. Simulated results show that the algorithm will significantly improve system throughput and performance while also lowering the computational complexity of the algorithm, enabling the whole system to have better communication quality.
... For allocating the resources, exact potential game and noncooperative game is used for power control optimization. 22 Further, distributed algorithm computes the Nash equilibrium point. 23 proposes an efficient scheme for energy optimization by limiting the number of users under some power constraints in a heterogeneous network upholding the QoS of the system. ...
Mm‐Wave communication ushers next‐gen communication to new heights guaranteeing higher speed and throughput. Enabling device‐to‐device (D2D) communication in next‐gen wireless communication is a Herculean task. This is due to introduction of pathloss attenuation by various environmental factors which deteriorates the signal. This article aims to minimize the effect of interference for quality reception of signals for D2D communication and increase system throughput. Thus, a power control scheme is proposed in underlay mode for uplink channel in mm‐Wave band. Here, D2D communication takes place through two modes namely, general mode and mm‐Wave mode. In presence of large number of proximity D2D users and increasing pathloss attenuation, it switches to mm‐Wave mode for communication. The formulated problem is converted to semiconvex form by expressing it into exponential form in Laplace domain. Our final objective is to maximize the energy efficiency (EE) of the proposed system under certain constraints. To reduce complexity of the problem, feasible regions of transmission power is introduced, that is, least and upper bounds which will ensure that power is maintained within a limit guaranteeing better throughput for D2D users. Enhanced EE and outage probability values also depict better performance of proposed system. Finally, fairness index (FI) shows that the proposed scheme yields better performance for the D2D users to communicate in the mm‐Wave band. A detailed comparison of FI for the proposed scheme is also done with other existing methods to prove the adequate performance of the proposed method. Simulation results also prove the efficacy of the proposed scheme.
... Control of transmission power of users through the implementation of a pure strategy based non-cooperative game theoretic model is one of the novel approaches to the problem of power control for D2D networks [18]. The non-cooperative game theoretic formulation for control of uplink transmission power in D2D underlay cellular networks can be paired with an exact potential game formulation to minimize interference for joint resource blocks to derive a Nash Equilibrium solution [19]. For D2D network conditions where convergence to a maximally energy efficient equilibrium is not possible, a Minimum Efficient Satisfaction Equilibrium (MESE) approach can be used to ensure desired QoS for users as well as the system as a whole [20]. ...
5G communication networks will dominate the global communications market in the next few years. Researchers working in the domain of 5G communication technologies are currently in the process of determining how device-to-device (D2D) communication networks may offer great benefits in urban metropolitan environments, due to their features. D2D networks can therefore offer an effective means to supplement the standard cellular communication networks, thereby reducing the load on the standard cellular networks while maintaining or enhancing the quality of service. In this work, we have discussed a user association scheme to determine optimal associations in D2D wireless networks based on game theory by deriving the Nash Equilibrium for games involving each pair of devices, using parameters such as SINR (signal to interference and noise ratio), path loss and battery charge remaining for each device acting as a node in the network. Further, we have developed an evolutionary game theoretic model for D2D link formation in the network when nodes are dynamically added, which, when simulated, can help identify an evolutionarily stable strategy or ESS.
... In [13], a Stackelberg game based interference suppression approach is proposed to control interference. In [14], Katsinis discusses about interference minimization and energy efficiency. The problem of joint resource block (RB) and uplink transmission power allocation in a D2D underlay cellular network is also elaborated. ...
... which can be taken to be on the efficient frontier of F. Equations [12][13][14][15] implies that, ...
... For example, Gu et al. in [22] designed a proportionally fair scheduling scheme for maximizing the logarithmic sum of data rates in D2D-cellular networks. A multi-stage decision making framework with joint resource block and power allocations for interference mitigation in D2D underlaid cellular networks was built and analyzed in [23]. However, since the joint multi-dimensional resource management for interference-aware D2D communications is vey challenging, existing works commonly restricted to simplified models with fixed transmission power, given link scheduling or single-channel scenarios [9]. ...
... s.t., (11) − (13), (19), (23), (25), Obviously, [P] is a mixed integer nonlinear programming problem (because of the binary integer decision variable x i,j and the nonlinear SINR constraint (23)), which is generally known to be NP-hard. Note that even by assuming all channels to be homogeneous (i.e., W m = W, G m i,j = G i,j , ∀m ∈ M), the problem may still be intractable due to the inherent symmetry property in the channel assignment, i.e., exchanging links assigned on any two channels does not change the objective function value but only altering the decision variables, and this will lead to an immeasurable complexity in searching the optimal result. ...
... 4. Although computation constraints in Section 3.1 are not explicitly expressed, all of them are implicitly considered in this formulation. Particularly, i) the deadline requirement of each task and its computation execution time are included in the transmission data rate constraint, and then implied by the SINR constraint (23); ii) the computation capacity constraints of the ES and each fog node are respectively transformed to constraint (25) and the restriction of set V i in the objective function; and iii) based on the relationship between end user's local processing and offloading decisions, a threshold requirement for its transmission energy cost is derived, which later becomes a power threshold in constraint (19). ...
In this paper, joint resource management for device-to-device (D2D) communication assisted multi-tier fog computing is studied. In the considered system model, each subscribed mobile end user can choose to offload its computation task to either an edge server deployed at the base station via the cellular connection or one nearby third-party fog node via the direct D2D connection. After receiving offloading requests from all end users, the network operator determines the optimal management of the fog computing system, including both computation and communication resource allocations, according to its service agreements with end users, energy cost of edge-server processing and total expense in renting third-party fog nodes. With the objective of maximizing the network management profit, a joint multi-dimensional resource optimization problem, integrating link scheduling, channel assignment and power control, is formulated. An optimal solution algorithm is proposed based on the idea of branch-and-price for addressing this complicated mixed integer nonlinear programming problem. To facilitate the practical implementation in large-scale systems, a suboptimal greedy algorithm with significantly reduced computational complexity is also developed. Simulation results examine the efficiency of the proposed D2D-assisted fog computing framework, and demonstrate the superiority of the proposed resource allocation algorithm over the counterparts.
... Instead, in our work to overcome these deficiencies, we adopt the philosophy of aiming satisfactory QoS [12,27,28] rather than targeting optimality in terms of QoS maximization [29]. Based on the discussion above, there are two driving factors behind this consideration. ...
Spectrum scarcity, combined with the tremendous increase of mobile users and their need for personalized services with different Quality of Service (QoS) requirements, fuel the necessity for the design of resource management approaches that ensure operation efficiency, flexibility and scalability. In this paper, we provide a novel theoretical framework to study several forms of efficient and stable system operation points, stemming from the concept of Satisfaction Equilibria, in the context of wireless communication networks. Considering a wireless communication environment under the presence of the Gaussian Interference Channel (GIC), a non-cooperative game among the users is studied, where the users aim in a selfish manner to meet their Quality of Service (QoS) prerequisite, in terms of data rate. We argue that instead of maximizing the QoS which is generally energy costly, better energy-efficiency is achieved by targeting satisfactory QoS levels only, thus obtaining Satisfaction Equilibria solutions. The sufficient and necessary conditions that lead to the Satisfaction Equilibrium are initially provided for the two-user case and the Efficient Satisfaction Equilibrium (ESE) is determined, where the users satisfy their QoS constraints with the lowest possible cost (i.e., power). An algorithmic approach following the best-response dynamics is provided to treat the multi-user case. To study and evaluate these equilibria operation points in a formal and quantitative manner, we coin some new theoretical concepts, namely the Price of Efficiency, Max Price of Efficiency and Max Price of Satisfaction, expressing the tradeoff of the achieved utility and the corresponding cost or the distance between the Satisfaction Equilibria of a given objective function. Finally, the performance evaluation of the proposed framework is obtained via modeling and simulation.
... However, if a D2D underlay system is considered in order to increase frequency reuse, control for co-channel interference is also required. Efficient interference management schemes for co-channel interference can be found in many papers [26][27][28][29][30] and can be used in addition to the techniques discussed in this paper. ...
Device-to-device (D2D) communication is a technique for direct communication between devices without going through a base station or other infrastructure. D2D communication technology has the advantages of improving spectrum efficiency and reducing transmission delay and transmission power. In D2D communication systems, orthogonal frequency-division multiple access (OFDMA) is widely used to maintain similarities with cellular communication systems and to secure transmission distance. OFDMA allows flexible and efficient use of frequency resources by allocating sub-channels independent to each user. In this paper, we consider a D2D overlay system that uses different sub-channels for cellular and D2D communications. In theory, the signals on different sub-channels of an OFDMA system are orthogonal and not interfered with each other. However, in a D2D communication system, which operates in a distributed manner, there is non-negligible interference from other sub-channels because of in-band emissions. In this paper, we address the performance degradation resulting from the interference from other sub-channels for OFDMA-based D2D group-casting systems. We consider three different scenarios of D2D relay, and we find the relay position that minimizes the outage probability. The simulation and analytical results show that the optimal location of a relay can be considerably different according to the source location and the target scenario.
... Thus, to address the uplink interference issue, an efficient resource management algorithm for D2D communications is necessary. The allocation of uplink resources in D2D communications occurs either in overlay or underlay inband cellular networks [4,5]. In an overlay scenario, different resources are assigned to both DPs and CUs. ...
Device-to-device (D2D) communications can be adopted as a promising solution to attain high quality of service (QoS) for a network. However, D2D communications generates harmful interference when available resources are shared with traditional cellular users (CUs). In this paper, network architecture for the uplink resource management issue for D2D communications underlaying uplink cellular networks is proposed. We develop a fractional frequency reuse (FFR) technique to mitigate interference induced by D2D pairs (DPs) to CUs and mutual interference among DPs in a cell. Then, we formulate a sum throughput optimization problem to achieve the QoS requirements of the system. However, the computational complexity of the optimization problem is very high due to the exhaustive search for a global optimal solution. In order to reduce the complexity, we propose a greedy heuristic search algorithm for D2D communications so as to find a sub-optimal solution. Moreover, a binary power control scheme is proposed to enhance the system throughput by reducing overall interference. The performance of our proposed scheme is analyzed through extensive numerical analysis using Monte Carlo simulation. The results demonstrate that our proposed scheme provides significant improvement in system throughput with the lowest computational complexity.
... D2D communication is defined as direct communication between two mobile users without traversing the base station [5,6], which can potentially increase the cellular capacity, improve the user throughput, and extend the battery lifetime of users [7]. In addition, the access to the spectrum in D2D communication can be done in two ways: Overlay spectrum sharing or underlay spectrum sharing [8,9]. In the overlay case, D2D transmitters can only access the channels which are not used by nearby cellular users. ...
In cellular networks, device-to-device communications can increase the spectrum efficiency, but some conventional schemes only consider uplink or downlink resource allocation. In this paper, we propose the joint uplink and downlink resource allocation scheme which maximizes the system capacity and guarantees the signal-to-noise-and-interference ratio of both cellular users and device-to-device pairs. The optimization problem is formulated as a mixed integer nonlinear problem that is usually NP hard. To achieve the reasonable resource allocation, the optimization problem is divided into two sub-problems including power allocation and channel assignment. It is proved that the objective function of power control is a convex function, in which the optimal transmission power can be obtained. The Hungarian algorithm is developed to achieve joint uplink and downlink channel assignment. The proposed scheme can improve the system capacity performance and increase the spectrum efficiency. Numerical results reveal that the performance of the proposed scheme of jointly uplink and downlink is better than that of the schemes for independent allocation.
... The problem of this work is that the power control method introduced in the paper was not optimal. A joint resource allocation and power control scheme for an underlay M-D2D communication was studied in [14]. The paper discussed a maximum weight bipartite matching-based resource allocation scheme and heuristic-based resource allocation scheme. ...
The sum throughput of a cellular network can be improved when nearby devices employ direct communications using a resource sharing technique. Multicast device-to-device (M-D2D) communication is a promising solution to accommodate higher transmission rates. In an M-D2D communication, a multicast group is formed by considering a transmitter that can transmit the same information to multiple receivers by considering the transmission link conditions. In this paper, we focus on the uplink interference generated due to the non-orthogonal sharing of resources between the cellular users and M-D2D groups. To mitigate the interference, we propose a spectrum reuse-based resource allocation and power control scheme for M-D2D communication underlaying an uplink cellular network. We formulate the throughput optimization problem by considering the fractional frequency reuse (FFR) method within a multicell cellular network. In addition, a metaheuristic-tabu search algorithm is developed that maximizes the probability of finding optimal solutions by minimizing uplink interference. To analyze fairness resource distribution among users, we finally consider Jain’s fairness index. Simulation results show that the proposed scheme can improve the coverage probability, success rate, spectral efficiency, and sum throughput of the network, compared with a random resource allocation scheme without a metaheuristic-tabu search algorithm.
