• ETRI Journal
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• v.44 no.3
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• pp.400-412
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• 2022

In cognitive radio networks (CRNs), the computational complexity of resource allocation algorithms is a significant problem that must be addressed. However, the high computational complexity of the optimal solution for tackling resource allocation in CRNs makes it inappropriate for use in practical applications. Therefore, this study proposes a power-based pricing algorithm (PPA) primarily to reduce the computational complexity in downlink CRN scenarios while restricting the interference to primary users to permissible levels. A two-stage approach reduces the computational complexity of the proposed mathematical model. Stage 1 assigns subcarriers to the CRN's users, while the utility function in Stage 2 incorporates a pricing method to provide a power algorithm with enhanced reliability. The PPA's performance is simulated and tested for orthogonal frequency-division multiplexing-based CRNs. The results confirm that the proposed algorithm's performance is close to that of the optimal algorithm, albeit with lower computational complexity of O(M log(M)).

• ETRI Journal
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• v.27 no.1
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• pp.43-52
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• 2005

In this paper, we introduce an adaptive radio resource allocation for IP-based mobile satellite services. We also present a synchronous multibeam CDMA satellite system using an orthogonal resource sharing mechanism among downlink beams for the adaptive packet transmission. The simulation results, using a Ka-band mobile satellite channel and various packet scheduling schemes, show that the proposed system and resource allocation scheme improves the beam throughput by more than two times over conventional systems. The simulation results also show that, in multibeam satellite systems, a system-level adaptation to a user's channel and interference conditions according to user locations and current packet traffic is more efficient in terms of throughput improvement than a user-level adaptation.

• Journal of Communications and Networks
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• v.14 no.6
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• pp.692-702
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• 2012

Supporting quality of service (QoS) guarantees for diverse multimedia services are the primary concerns for WiMAX (IEEE 802.16) networks. A scheduling scheme that satisfies QoS requirements has become more important for wireless communications. We propose a downlink scheduling scheme called adaptive priority-based downlink scheduling (APDS) for providing QoS guarantees in IEEE 802.16 networks. APDS comprises two major components: Priority assignment and resource allocation. Different service-type connections primarily depend on their QoS requirements to adjust priority assignments and dispatch bandwidth resources dynamically. We consider both starvation avoidance and resource management. Simulation results show that our APDS methodology outperforms the representative scheduling approaches in QoS satisfaction and maintains fairness in starvation prevention.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.4
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• pp.385-398
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• 2009

This paper aims to find a suitable solution to joint allocation of sub-channel and transmit power for multiple users in an IEEE 802.16e OFDMA/TDD cellular system. We propose the FASA (Fairness insured Aggressive Sub-channel Allocation) algorithm, which is a dynamic channel allocation algorithm that considers all of the users' channel state information conditionally in order to maximize throughput while taking into account fairness. A dynamic power allocation algorithm, i.e., an improved CHC algorithm, is also proposed in combination with the FASA algorithm. It collects the extra downlink transmit power and re-allocates it to other potential users. Simulation results show that the joint allocation scheme with the improved CHC power allocation algorithm provides an additional increase of sector throughput while simultaneously enhancing fairness. Four frames of time delay for CQI feedback and scheduling are considered. Furthermore, by addressing the difference between uplink and downlink scheduling in an IEEE 802.16e OFDMA TDD system, we can employ the uplink channel information directly via channel sounding, resulting in more accurate uplink dynamic resource allocation.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.261-262
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• 2008

TD-SCDMA is considered as an innovative Chinese 3G technology adopted by the ITU for the IMT-2000 family. TD-SCDMA combines TDMA and CDMA components to provide more efficient use of radio resources. However, the downlink scheduler of TD-SCDMA should transmit data packets with the initial configuration and cannot change the configuration dynamically. Therefore, in this paper, we propose an enhanced channel allocation, by which mobile terminals can share the downlink channelization codes dynamically.

• Journal of Communications and Networks
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• v.12 no.1
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• pp.30-42
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• 2010

In this work we consider the problem of downlink resource allocation for proportional fairness of long term received rates of data users and quality of service for real time sessions in an OFDMA-based wireless system. The base station allocates available power and subchannels to individual users based on long term average received rates, quality of service (QoS) based rate constraints and channel conditions. We formulate and solve a joint bandwidth and power optimization problem, solving which provides a performance improvement with respect to existing resource allocation algorithms. We propose schemes for flat as well as frequency selective fading cases. Numerical evaluation results show that the proposed method provides better QoS to voice and video sessions while providing more and fair rates to data users in comparison with existing schemes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1471-1488
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• 2018

Interference mitigation is a significant issue in the cognitive heterogeneous networks, this paper studied how to reduce the interference to macrocell users (MU) and improve system throughput. Establish the interference model with imperfect spectrum sensing by analyzing the source of interference complexity. Based on the user topology, the optimize problem was built to maximize the downlink throughput under given interference constraint and the total power constraint. We decompose the resource allocation problem into subcarrier allocation and power allocation. In the subcarrier assignment step, the allocated number of subcarriers satisfies the requirement of the femtocell users (FU).Then, we designed the power allocation algorithm based on the Lagrange multiplier method and the improved water filling method. Simulation results and performance analyses show that the proposed algorithm causes less interference to MU than the algorithm without considering imperfect spectrum sensing, and the system achieves better throughput performance.

• Journal of Communications and Networks
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• v.18 no.3
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• pp.420-428
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• 2016

In this paper, we investigate the scheduling and power allocation for coordinated multi-point transmission in downlink long term evolution advanced (LTE-A) systems, where orthogonal frequency division multiple-access is used. The proposed scheme jointly optimizes user selection, power allocation, and modulation and coding scheme (MCS) selection to maximize the weighted sum throughput with fairness consideration. Considering practical constraints in LTE-A systems, the MCSs for the resource blocks assigned to the same user need to be the same. Since the optimization problem is a combinatorial and non-convex one with high complexity, a low-complexity algorithm is proposed by separating the user selection and power allocation into two subproblems. To further simplify the optimization problem for power allocation, the instantaneous signal-to-interference-plus-noise ratio (SINR) and the average SINR are adopted to allocate power in a single cell and multiple coordinated cells, respectively. Simulation results show that the proposed scheme can improve the average system throughput and the cell-edge user throughput significantly compared with the existing schemes with limited feedback.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.1
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• pp.20-39
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• 2020

This paper considers a downlink multi-carrier cooperative non-orthogonal multiple access (NOMA) transmission, where no direct link exists between the far user and the base station (BS), and the communication between them only relies on the assist of the near user. Firstly, the BS sends a superimposed signal of the far and the near user to the near user, and then the near user adopts simultaneous wireless information and power transfer (SWIPT) to split the received superimposed signal into two portions for energy harvesting and information decoding respectively. Afterwards, the near user forwards the signal of the far user by utilizing the harvested energy. A minimum data is required to ensure the quality of service (QoS) of the far user. We jointly optimize power allocation, subcarrier allocation, time allocation, the power allocation (PA) coefficient and the power splitting (PS) ratio to maximize the number of data bits received at the near user under the energy causality constraint, the minimum data constraint and the transmission power constraint. The block-coordinate descent method and the Lagrange duality method are used to obtain a suboptimal solution of this optimization problem. In the final simulation results, the superiority of the proposed NOMA scheme is confirmed compared with the benchmark NOMA schemes and the orthogonal multiple access (OMA) scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1569-1586
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• 2015

This paper considers the optimal cell association and resource allocation for load balancing in a heterogeneous cellular network subject to user's quality-of-service (QoS) constraints. We adopt the proportional fairness (PF) utility maximization formulation which also accommodates the QoS constraints in terms of minimum rate requirements. With equal resource allocation this joint optimization problem is either infeasible or requires relaxation that yields a solution which is difficult to implement. Nevertheless, we show that this joint optimization problem can be effectively solved without any priori assumption on resource allocation and yields a cell association scheme which enforces single BS association for each user. We re-formulated the joint optimization problem as a network-wide resource allocation problem with cardinality constraints. A reweighted heuristic l₁-norm regularization method is used to obtain a sparse solution to the re-formulated problem. The cell association scheme is then derived from the sparsity pattern of the solution, which guarantees a single BS association for each user. Compared with the previously proposed method based on equal resource allocation, the proposed framework results in a feasible cell association scheme and yields a robust solution on resource allocation that satisfies the QoS constraints. Our simulations illustrate the impact of user's minimum rate requirements on cell association and demonstrate that the proposed approach achieves load balancing and enforces single BS association for users.