• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.7
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• pp.36-44
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• 2010

When multi-user MIMO (Multiple-Input Multiple-Output) systems utilize a sum-rate maximization (SRM) scheduler, the throughput of the systems can be enhanced. However, fairness problems may arise because users located near cell edge or experiencing poor channel conditions are less likely to be selected by the SRM scheduler. In this paper, a weighted sum-rate maximization (WSRM) scheduler is used to enhance the fairness performance of the MIMO systems. Closed-form expressions for the optimal transmit power allocation of WSRM and corresponding weighted sum-rate (WSR) are derived in the 6-sector collaborative transmission system. Using the derived results, we propose an algorithm which searches the optimal power allocation for WSRM in the 3-sector collaborative transmission system. Based on the derived closed-form expressions and the proposed algorithm, we perform computer simulations to compare performance of the WSRM scheduler and the SRM scheduler with respect to the sum-rate and the log-sum-of-average rates. We further verify that the WSRM scheduler efficiently improves fairness performance by showing the enhanced performance of average transmission rates in low percentile region.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.583-585
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• 2016

The recent advances in wireless networks area have led to new techniques, such as small cells or full-duplex (FD) transmission, have also been developed to further increase the network capacity. Particularly, full-duplex communication promises expected throughput gain by doubling the spectrum compared to half-duplex (HD) communication. Because this technique permits one set of frequencies to simultaneously transmit and receive signals. In this paper, we focus on the binary power control for the users and the base stations in full-duplex multiple cellulars wireless networks to obtain optimal sum-rate under the effect interference and noise. We investigate with a scenario in there one carrier is assigned to only one user in each cell and construct a model for this problem. In this work, we apply the binary power control by the its simplification in the implemented algorithm for both uplink and downlink simultaneously to maximize sum data rate of the system. At first, we realize the 2-cells case separately to check the optimal power allocation whether being binary. Then, we carry on with N-cells case in general through properties of binary power control.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.3887-3907
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• 2015

This paper introduces a full duplex single secondary user multiple-input multiple-output (FD-SSU-MIMO) cognitive radio network, where secondary user (SU) opportunistically accesses the authorized spectrum unoccupied by primary user (PU) and transmits data based on FD-MIMO mode. Then we study the network achievable average sum-rate maximization problem under sum transmit power budget constraint at SU communication nodes. In order to solve the trade-off problem between SU's sensing time and data transmission time based on opportunistic spectrum access (OSA) and the power allocation problem based on FD-MIMO transmit mode, we propose a simple trisection algorithm to obtain the optimal sensing time and apply an alternating optimization (AO) algorithm to tackle the FD-MIMO based network achievable sum-rate maximization problem. Simulation results show that our proposed sensing time optimization and AO-based optimal power allocation strategies obtain a higher achievable average sum-rate than sequential convex approximations for matrix-variable programming (SCAMP)-based power allocation for the FD transmission mode, as well as equal power allocation for the half duplex (HD) transmission mode.

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

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.6
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• pp.1926-1945
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• 2014

In this paper, we propose a distributed signal subspace interference alignment algorithm for single beam K-user ($3K{\geq}$) MIMO interference channel based on sum rate maximization and game theory. A framework of game theory is provided to study relationship between interference signal subspace and altruistic-egoistic bayesian game cost function. We demonstrate that the asymptotic interference alignment under proposed scheme can be realized through a numerical algorithm using local channel state information at transmitters and receivers. Simulation results show that the proposed scheme can achieve the total degrees of freedom that is equivalent to the Cadambe-Jafar interference alignment algorithms with perfect channel state information. Furthermore, proposed scheme can effectively minimize leakage interference in desired signal subspace at each receiver and obtain a moderate average sum rate performance compared with several existing interference alignment schemes.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.109-110
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• 2007

The sum-rate capacity of multi-antenna broadcast channels recently has attracted much research interests. However, those effort mainly has focused on a single-cell system. In this paper, we consider a multi-cell system where a transmitter uses zero-forcing beamforming with multiple antennas. We select a linear zero-forcing weight that maximizes the sum-rate when intercell interference exists. With numerical investigation, we will show the sum-rate gain achieved by the proposed method gets larger when the number of interfering cells increases.

• Journal of Information Processing Systems
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• v.17 no.2
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• pp.306-317
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• 2021

The unbalance between system ergodic sum rate and high fairness is one of the key issues affecting the performance of non-orthogonal multiple access (NOMA) system. To solve the problem, this paper proposes a power allocation algorithm to realize the ergodic sum rate maximization of NOMA system. The scheme is mainly achieved by the construction algorithm of fair model based on α fair utility function and the optimal solution algorithm based on the interior point method of penalty function. Aiming at the construction of fair model, the fair target is added to the traditional power allocation model to set the reasonable target function. Simultaneously, the problem of ergodic sum rate and fairness in power allocation is weighed by adjusting the value of α. Aiming at the optimal solution algorithm, the interior point method of penalty function is used to transform the fair objective function with unequal constraints into the unconstrained problem in the feasible domain. Then the optimal solution of the original constrained optimization problem is gradually approximated within the feasible domain. The simulation results show that, compared with NOMA and time division multiple address (TDMA) schemes, the proposed method has larger ergodic sum rate and lower Fairness Index (FI) values.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.7
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• pp.23-28
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• 2010

We propose a reference vector diversity method in multi-cell multi-user uplink system with the subspace interference alignment to obtain higher sum rate capacity. The proposed method transmits several reference vectors before the data transmission, and selects the best reference vector to maximize the cell sum rate. The proposed method provides higher sum-rate capacity compared with the previous interferenc alignment. Simulation result exhibits the proposed method improves the sum-rate capacity by 60%.

• Journal of Communications and Networks
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• v.14 no.2
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• pp.151-161
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• 2012

This paper considers a two-user Gaussian interference channel with energy harvesting transmitters. Different than conventional battery powered wireless nodes, energy harvesting transmitters have to adapt transmission to availability of energy at a particular instant. In this setting, the optimal power allocation problem to maximize the sum throughput with a given deadline is formulated. The convergence of the proposed iterative coordinate descent method for the problem is proved and the short-term throughput maximizing offline power allocation policy is found. Examples for interference regions with known sum capacities are given with directional water-filling interpretations. Next, stochastic data arrivals are addressed. Finally, online and/or distributed near-optimal policies are proposed. Performance of the proposed algorithms are demonstrated through simulations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.4C
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• pp.414-423
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• 2009

This paper considers a linear precoding scheme that achieves near optimal sum rate. While the minimum mean square error (MMSE) precoding provides the better MSE performance at all signal-to-noise ratio (SNR) than the zero forcing (ZF) precoding, its sum rate shows superior performance to ZF precoding at low SNR but inferior performance to ZF precoding at high SNR, From this observation, we first propose a near optimal linear precoding scheme in terms of sum rate. The resulting precoding scheme regularizes ZF precoding to maximize the sum rate, resulting in better sum rate performance than both ZF precoding and MMSE precoding at all SNR ranges. To find regularization parameters, we propose a simple algorithm such that locally maximal sum rate is achieved. As a low complexity alternative, we also propose a simple power re-allocation scheme in the conventional regularized channel inversion scheme. Finally, the proposed scheme is tested under the presence of channel estimation error. By simulation, we show that the proposed scheme can maintain the performance gain in the presence of channel estimation error and is robust to the channel estimation error.