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Then the insights gained from the optimality conditions will be combined to propose a suboptimal algorithm for SPA in the following section.
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We propose a suboptimal algorithm, called particle swarm optimization (PSO), for partial transmit sequence active interference cancellation (PTS-AIC) used for interference avoidance feature for UWB OFDM transmitter, to reduce the computational complexity significantly.
To provide feasible estimator with affordable complexity, we propose a suboptimal algorithm, which can be viewed as a modified expectation-maximization (EM) algorithm [24].
Thus, to reduce the complexity, we propose a suboptimal algorithm that separates the resource allocation into two steps: subcarrier allocation and power allocation.
In the following, we derive a suboptimal algorithm for the case with unknown CSI.
Of course, the SL0 is a suboptimal algorithm for the DOA estimate.
We propose a suboptimal distributed algorithm for power minimization subject to a common rate constraint based on the iterative water-filling algorithm initially derived for dynamic spectrum management in digital subscriber line (DSL) [19].
We use the optimality conditions for this problem to propose a suboptimal allocation algorithm.
Here, we also propose a suboptimal distributed algorithm.
To cope with high time complexity of finding an optimal decomposition, we propose a suboptimal heuristic algorithm.
For each objective, we first derive an optimal user selection criterion and then propose a suboptimal distributed algorithm with low complexity.
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