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Many publications study the problem of maximizing sum capacity [3,7-9].
Among feedback users, the base station schedules users using the criterion of maximizing sum capacity.
Subsequently, we formulate the problem of maximizing sum capacity while satisfying the minimum capacity requirements for each femtocell.
Among feedback users, the base station schedules a subset of users using the criterion of maximizing sum capacity.
We formulate these concerns as a constrained optimization problem with the objective function of maximizing sum capacity.
Among feedback users, the base station assigns a user to the unallocated beam vector of the selected subcodebook using the criterion of maximizing sum capacity.
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In this paper, we are more interested in the optimal power allocation policy that maximizes sum capacity of non-real-time users in multiple access channel (MAC).
But, unlike the interference-free ZF, the problem of maximizing sum-rate capacity using CIR precoding becomes nonconvex, which cannot be solved by water-filling strategy.
Also, maximizing the sum capacity is not always an appropriate optimization criterion for realistic network scenarios since users usually have asymmetric channel statistics.
Since each link does not have information about other channels in the network, the antenna configuration decision cannot be geared toward maximizing network sum capacity.
Optimal power allocation for maximizing the sum capacity of multiple access channel (MAC) with quality-of-service (QoS) constraints is investigated in this paper.
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