• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4738-4758
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• 2017

Resource allocation plays a crucial role in multiuser multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM) systems to improve overall system performance. While previously proposed resource allocation algorithms are mainly designed from the point of view of the information-theoretic, we formulate the resource allocation problem as an average bit error rate (BER) minimization problem subject to a total power constraint when considering employing realistic MIMO detection techniques. Subsequently, we derive the optimal subcarrier and power allocation algorithms for three types of well-known MIMO detectors, including the maximum likelihood (ML) detector, linear detectors, and successive interference cancellation (SIC) detectors. To reduce the complexity, we also propose a two-step suboptimal algorithm that separates subcarrier and power allocation for each detector. We also analyze the diversity gain of the proposed suboptimal algorithms for various MIMO detectors. Simulation results confirm that the proposed suboptimal algorithm for each detector can achieve a comparable performance with the optimal allocation with a much lower complexity. Moreover, it is shown that the suboptimal algorithms perform better than the conventional algorithms that are known in the literature.

• Proceedings of the IEEK Conference
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• 2001.06a
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• pp.357-360
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• 2001

In this paper, we propose and evaluate a new interference cancellation method using low pass filtered data estimation method of the instantaneous decision sawnle obtained from each decision stage. With respect to the convergence to the optimal solution the superiority of the proposed method to parallel interference cancellation (PIC) referred as prevailing techniques is proved by its (asymptotic) spectral radius. Through the simulation under the various environment, we show the performance superiority of the IC scheme using proposed method to the PIC scheme. Furthermore, we show transcendence of the proposed method on the possibility of multirate transmission or multiple power scheduling and of performance in the various traffic environments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.12
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• pp.3061-3080
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• 2012

To improve the sensing performance, cooperation among secondary users can be utilized to collect space diversity. In this paper, we focus on the optimization of cooperative spectrum sensing in which multiple cognitive users efficiently cooperate to achieve superior detection accuracy with minimum sensing error probability in multiple cross-over cognitive radio networks. The analysis focuses on two fusion strategies: soft information fusion and hard information fusion. Under soft information fusion, the optimal threshold of the energy detector is derived in both noncooperative single-user and cooperative multiuser sensing scenarios. Under hard information fusion, the optimal randomized rule and the optimal decision threshold are derived according to the rule of minimum sensing error (MSE). MSE rule shows better performance on improving the final false alarm and detection probability simultaneously. By simulations, our proposed strategy optimizes the sensing performance for each cognitive user which is randomly distributed in the multiple cross-over cognitive radio networks.

• Journal of Communications and Networks
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• v.8 no.3
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• pp.313-322
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• 2006

We consider a power controlled code division multiple access (CDMA) system with multiple flow types. At each of the N nodes, there are F flow types with different signal-to-interference-and-noise-ratio (SINR) requirements. To keep the complexity of the transmitter low, we assume that each node uses the same power level for all its flows. The single flow case has been fully solved and is well-understood. We concentrate on the multiple flow case, and use a novel and different approach. For the uplink problem with N = 2 and F arbitrary, the necessary and sufficient conditions to have a solution are found and proved. For the general N > 1 uplink problem, we provide a necessary condition for the problem to have a solution and an iterative algorithm to find the optimum solution. For the downlink case with F > 1 some properties of the optimal sequences are obtained.