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Furthermore, closed-form power allocation solutions which minimize the outage probability or maximizes the ergodic rate were presented using the high SNR approximations.

The optimal power allocation strategy that maximizes the ergodic sum capacity and the capacity region in the uplink of a multiuser MIMO wireless system has been extensively investigated in this chapter.

In this paper, we have presented a resource allocation method that maximizes the ergodic weighted-sum rate of a multiuser mobile WiMAX while satisfying user's specific minimum rate demand and system fairness requirement for a given power budget.

In this paper, we investigate the power allocation scheme that maximizes the ergodic rate based on the network geometry and the statistical CSI which include the second-order statistics and the interference level.

Similar(56)

For relay networks, we have formulated power allocation problem to maximize the ergodic capacity under total power constraint.

The optimal array deployments obtained according to this criterion are then shown, via numerical optimization, to maximize the ergodic capacity for the scenarios considered here.

Under the OPC and average/peak TPCs, optimal power allocation strategies have been developed to maximize the ergodic and outage capacities of SU systems in [83].

In [14], an optimization problem is formulated to maximize the ergodic capacity of SUs over transmission power and sensing time, by assuming a constant detection threshold.

A joint sensing time and power allocation scheme has been studied in [127] under the average IPCs and TPCs to maximize the ergodic throughput of SU systems.

The objective is to maximize the ergodic weighted sum rate under long-term fairness, minimum data rate requirement, and power budget constraints.

Under the unrealistic perfect CSIT assumption, instead of maximizing the ergodic or the expected weighted-sum rate, the optimization goal is to maximize the instantaneous weighted-sum rate (38).

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