• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.11
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• pp.2576-2583
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• 2015

In a full-duplex (FD) wireless cellular network, uplink (UL) users induce the severe inter-user interference to downlink (DL) users. Therefore, a user scheduling that makes a pair of DL user and UL user to use the same radio resource simultaneously influences the system performances significantly. In this paper, we first formulate an optimization problem for user scheduling to minimize the occurrence of outage, aiming to guarantee the quality of service of users, and then we propose a suboptimal user scheduling algorithm with low complexity. The proposed scheduling algorithm is designed in a way where the DL user with a worse signal quality has a higher priority to choose its UL user that causes less interference. Simulation results show that the FD system using the proposed user scheduling algorithm achieves the optimal performance and significantly decreases the outage probability compared with the conventional half-duplex cellular system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.3876-3895
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• 2014

Recently, Heterogeneous Network (HetNet) with Coordinated Multi-Point (CoMP) scheme is introduced into Long Term Evolution-Advanced (LTE-A) systems to improve digital services for User Equipments (UEs), especially for cell-edge UEs. However, Radio Resource Management (RRM), including Resource Block (RB) scheduling and Power Allocation (PA), in this scenario becomes challenging, due to the intercell cooperation. In this paper, we investigate the RRM problem for downlink transmission of HetNet system with Joint Processing (JP) CoMP (both joint transmission and dynamic cell selection schemes), aiming at maximizing weighted sum data rate under the constraints of both transmission power and backhaul capacity. First, joint RB scheduling and PA problem is formulated as a constrained Mixed Integer Programming (MIP) which is NP-hard. To simplify the formulation problem, we decompose it into two problems of RB scheduling and PA. For RB scheduling, we propose an algorithm with less computational complexity to achieve a suboptimal solution. Then, according to the obtained scheduling results, we present an iterative Karush-Kuhn-Tucker (KKT) method to solve the PA problem. Extensive simulations are conducted to verify the effectiveness and efficiency of the proposed algorithms. Two kinds of JP CoMP schemes are compared with a non-CoMP greedy scheme (max capacity scheme). Simulation results prove that the CoMP schemes with the proposed RRM algorithms dramatically enhance data rate of cell-edge UEs, thereby improving UEs' fairness of data rate. Also, it is shown that the proposed PA algorithms can decrease power consumption of transmission antennas without loss of transmission performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.10A
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• pp.896-905
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• 2005

In this paper, we propose a SPD(Selective Packet Delay) scheme to improve the performance of High-Speed Downlink Shared Channel(HS-DSCH) employing N-Channel Stop and Wait retransmission scheme in High Speed Downlink Packet Access(HSDPA) system. The proposed SPD coordinates packet transmissions according to the channel condition. When the channel condition is bad, packet transmission is forcedly delayed, and the designated time slot is set over to other users in good channel condition. Hence, the SPD is able to reduce the average transmission delay for packet transmission under the burst error environments. In addition, we propose two packet scheduling schemes called SPD-LDPF(Long Delayed Packet First) and SPD-DCRR(Deficit Compensated Round Robin) that are effectively combined with the SPD scheme. Simulation results show that the proposed scheme has better performance in terms of delay, throughput and fairness.

• Journal of Communications and Networks
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• v.16 no.1
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• pp.1-9
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• 2014

Block diagonalization (BD) has been proposed as a simple and effective technique in multiuser multiple-input multiple-output (MU-MIMO) broadcast channels. However, when channel state information (CSI) knowledge is limited at the transmitter, the performance of the BD may be degraded because inter-user interference cannot be completely eliminated. In this paper, we propose an efficient CSI quantization technique for BD precoded systems with limited feedback where users supported by a base station are selected by dynamic scheduling. First, we express the received signal-to-interference-plus-noise ratio (SINR) when multiple data streams are transmitted to the user, and derive a lower bound expression of the expected received SINR at each user. Then, based on this measure, each user determines its quantized CSI feedback information which maximizes the derived expected SINR, which comprises both the channel direction and the amplitude information. From simulations, we confirm that the proposed SINR-based channel quantization scheme achieves a significant sum rate gain over the conventional method in practical MU-MIMO systems.

• Journal of Communications and Networks
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• v.13 no.3
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• pp.232-239
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• 2011

This paper investigates the user selection problem of successive zero-forcing precoded multiuser multiple-input multiple-output (MU-MIMO) downlink systems, in which the base station and mobile receivers are equipped with multiple antennas. Assuming full knowledge of the channel state information at the transmitter, dirty paper coding (DPC) is an optimal precoding strategy, but practical implementation is difficult because of its excessive complexity. As a suboptimal DPC solution, successive zero-forcing DPC (SZF-DPC) was recently proposed; it employs partial interference cancellation at the transmitter with dirty paper encoding. Because of a dimensionality constraint, the base station may select a subset of users to serve in order to maximize the total throughput. The exhaustive search algorithm is optimal; however, its computational complexity is prohibitive. In this paper, we develop two low-complexity user scheduling algorithms to maximize the sum rate capacity of MU-MIMO systems with SZF-DPC. Both algorithms add one user at a time. The first algorithm selects the user with the maximum product of the maximum column norm and maximum eigenvalue. The second algorithm selects the user with the maximum product of the minimum column norm and minimum eigenvalue. Simulation results demonstrate that the second algorithm achieves a performance similar to that of a previously proposed capacity-based selection algorithm at a high signal-to-noise (SNR), and the first algorithm achieves performance very similar to that of a capacity-based algorithm at a low SNR, but both do so with much lower complexity.