• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.35 no.8A
• /
• pp.743-751
• /
• 2010

OFDMA femtocell becomes an effective solution to support indoor high data rate services instead of the macrocell systems. Although the advantage of the femtocell, the co-channel interference between the femocell and the macrocell is the most significant problem that reduces the system performance. Macrocell users who have no permission to access the femtocell suffer from interference of the downlink transmission of femtocell. Therefore, the femtocell should use transmission power as small as possible to reduce interference to macrocell users. In this paper, we define the margin adaptive power allocation problem for the femtocell and propose a heuristic power allocation algorithm to solve the problem. Simulation results show the performance of the proposed algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.10
• /
• pp.4923-4939
• /
• 2019

In this paper, a secure transmission scheme based on the artificial noise is proposed for D2D communications underlaying the full-duplex cellular network, and a secure power allocation scheme to maximize the overall secrecy rate of both the cellular user and D2D transmitter node is presented. Firstly, the full-duplex base station transmits the artificial noise to guarantee the secure communications when it receives signals of cellular uplinks. Under this secure framework, it is found that improving the transmission power of the cellular user or the D2D transmitter node will degrade the secrecy rate of the other, although will improve itself secrecy rate obviously. Hence, a secure power allocation scheme to maximize the overall secrecy rate is presented subject to the security requirement of the cellular user. However, the original power optimization problem is non-convex. To efficiently solve it, we recast the original problem into a convex program problem by utilizing the proper relaxation and the successive convex approximation algorithm. Simulation results evaluate the effectiveness of the proposed scheme.

• International Journal of Computer Science & Network Security
• /
• v.22 no.7
• /
• pp.199-205
• /
• 2022

The extensive growth in data rate demand by the smart gadgets and mobile broadband application services in wireless cellular networks. To achieve higher data rate demand which leads to aggressive frequency reuse to improve network capacity at the price of Inter Cell Interference (ICI). Fractional Frequency Reuse (FFR) has been recognized as an effective scheme to get a higher data rate and mitigate ICI for perfect geometry network scenarios. In, an irregular geometric multicellular network, ICI mitigation is a challenging issue. The purpose of this paper is to develop distributed dynamic power allocation scheme for FFR based on game theory to mitigate ICI. In the proposed scheme, each cell region in an irregular multicellular scenario adopts a self-less behavior instead of selfish behavior to improve the overall utility function. This proposed scheme improves the overall data rate and mitigates ICI.

• Journal of Information Processing Systems
• /
• v.17 no.4
• /
• pp.721-736
• /
• 2021

For the mobile edge computing (MEC) system supporting dense network, a joint allocation algorithm of computing and communication resources based on reinforcement learning is proposed. The energy consumption of task execution is defined as the maximum energy consumption of each user's task execution in the system. Considering the constraints of task unloading, power allocation, transmission rate and calculation resource allocation, the problem of joint task unloading and resource allocation is modeled as a problem of maximum task execution energy consumption minimization. As a mixed integer nonlinear programming problem, it is difficult to be directly solve by traditional optimization methods. This paper uses reinforcement learning algorithm to solve this problem. Then, the Markov decision-making process and the theoretical basis of reinforcement learning are introduced to provide a theoretical basis for the algorithm simulation experiment. Based on the algorithm of reinforcement learning and joint allocation of communication resources, the joint optimization of data task unloading and power control strategy is carried out for each terminal device, and the local computing model and task unloading model are built. The simulation results show that the total task computation cost of the proposed algorithm is 5%-10% less than that of the two comparison algorithms under the same task input. At the same time, the total task computation cost of the proposed algorithm is more than 5% less than that of the two new comparison algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.35 no.12C
• /
• pp.1020-1028
• /
• 2010

Relay has attracted great attention due to its inherent capability to extend the service coverage and combat shadowing in next generation mobile communication systems. So far, most relay technologies have been developed under the half-duplex (HD) constraint that prevents relays from transmitting and receiving at the same time. Although half-duplex relay (HDR) is easy to implement, it requires partitioning of resource for transmission and reception, reducing the whole system capacity. In this paper, we propose a multinser precoding and power control scheme with sum rate matching for a full-duplex (FD) multiple-input multiple-output (MIMO) relay. Full-duplex relay (FDR) can overcome the drawback of HDR by transmitting and receiving on the same frequency at the same time, while it is crucial to reduce the effect of self-interference that is caused by its own transmitter to its own receiver. The proposed precoding scheme cancels the self-interference of the FDR as well as to support multiuser MIMO. Moreover, we suggest a power allocation scheme for FD MIMO relay with the constraint that the sum rate of the relay's received data streams is equal to that of the relay's transmit data streams.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.5
• /
• pp.2081-2101
• /
• 2016

Successive interference cancellation (SIC) is considered to be a promising technique to mitigate multi-user interference and achieve concurrent uplink transmissions, but the optimal power allocation (PA) issue for SIC users is not well addressed. In this article, we focus on the optimization of the PA ratio of users on an SIC channel and analytically obtain the optimal PA ratio with regard to the signal-to-interference-plus-noise ratio (SINR) threshold for successful demodulation and the sustainable demodulation error rate. Then, we design an efficient resource allocation (RA) scheme using the obtained optimal PA ratio. Finally, we compare the proposal with the near-optimum RA obtained by a simulated annealing search and the RA scheme with random PA. Simulation results show that our proposal achieves a performance close to the near-optimum and much higher performance than the random scheme in terms of total utility and Jain's fairness index. To demonstrate the applicability of our proposal, we also simulate the proposal in various network paradigms, including wireless local area network, body area network, and vehicular ad hoc network.

• Journal of Communications and Networks
• /
• v.4 no.3
• /
• pp.199-208
• /
• 2002

The downlink rate scheduling problem is considered for CDMA networks with multiple users carrying packets of heterogeneous traffic (voice/audio only, bursty data only or mixed traffic), with each type having its own distinct quality of service requirements. Several rate scheduling algorithms are developed, the common factor of which is that part of the decision on which users to serve is based on a function of the deadline of their head-ofline packets. An approach of Andrews et al., in which the basic Earliest-Deadline-First algorithm is studied for similar systems, is extended to result in better performance by considering a more efficient power usage and by allowing service of more than one user per timeslot if the power resources permit it. Finally, the performance of the proposed schemes is compared through simulations.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.5
• /
• pp.2015-2028
• /
• 2016

In this paper, we propose a sum transmission rate maximization based cooperative spectrum sharing protocol with quality-of-service (QoS) support for both of the primary and secondary systems, which exploits the situation when the primary system experiences a weak channel. The secondary transmitter ST_b which provides the best performance for the primary and secondary systems is selected to forward the primary signal. Specifically, ST_b helps the primary system achieve the target rate by using a fraction of its power to forward the primary signal. As a reward, it can gain spectrum access by using the remaining power to transmit its own signal. We study the secondary user selection and optimal power allocation such that the sum transmission rate of primary and secondary systems is maximized, while the QoS of both primary and secondary systems can be guaranteed. Simulation results demonstrate the efficiency of the proposed spectrum sharing protocol and its benefit to both primary and secondary systems.

• ETRI Journal
• /
• v.42 no.6
• /
• pp.846-858
• /
• 2020

The non-orthogonal multiple access (NOMA) technique offers throughput improvement to meet the demands of the future generation of wireless communication networks. The objective of this work is to further improve the throughput by including an underlay cognitive radio network with an existing multi-carrier NOMA network, using cooperative communication. The throughput is maximized by optimal resource allocation, namely, power allocation, subcarrier assignment, relay selection, user pairing, and subcarrier pairing. Optimal power allocation to the primary and secondary users is accomplished in a way that target rate constraints of the primary users are not affected. The throughput maximization is a combinatorial optimization problem, and the computational complexity increases as the number of users and/or subcarriers in the network increases. To this end, to reduce the computational complexity, a dynamic network resource allocation algorithm is proposed for combinatorial optimization. The simulation results show that the proposed network improves the throughput.

• International Journal of Internet, Broadcasting and Communication
• /
• v.12 no.3
• /
• pp.39-45
• /
• 2020

The fifth generation (5G) mobile communication has been more commercialized worldwide. One of the promising 5G technologies is non-orthogonal multiple access (NOMA). We present the achievable sum rate of non-orthogonal multiple access (NOMA) with correlated superposition coding (SC). Then this paper investigates the impacts of correlation on the achievable sum rate of correlated SC NOMA. It is shown that the achievable sum rate of correlated SC NOMA is greater than that of standard independent SC NOMA, for the most of the values of the power allocation factor over the meaningful range of the user fairness. In result, correlated SC could be a promising scheme for NOMA.