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In this paper, we present a novel bit allocation and rate control algorithm for compressed domain video transcoding.
The work done in [16, 17] jointly addresses resource allocation and rate adaptation for Scalable Video Coding SVCC) traffic.
Zhang et al. [11] proposed regional bit allocation and rate distortion (RD) optimization algorithms for multi-view depth video coding using the imbalance bitrate allocation for different regions.
The system value-based sum capacity/throughput maximization methods for optimum signature sequence selection, energy allocation, and rate maximization methods will be described in Section 6.
Radio resource management (RRM) techniques such as admission control, scheduling, subcarrier allocation, channel assignment, power allocation, and rate control are essential for maximizing the resource utilization and providing quality of service (QoS) in wireless networks.
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where past allocations and rates, {p τ,1 ≤ τ < t} and {rk,n,τ,1 ≤ τ < t}, and past and current channels, {Hk,n,τ,1 ≤ τ ≤ t,∀k,n}, are known.
The base station may have knowledge of past allocations and rates, {p τ,1 ≤ τ < t} and {rk,n,τ,1 ≤ τ < t}, and past and current channels, {Hk,n,τ,1 ≤ τ ≤ t,∀k,n}.
In the second step, we optimize the bit allocation and code rate according to the greedy algorithm outlined in 4.3.
For comparison with the network coding case, we also optimize the time allocation and the rate ratio.
We generate 1000 realizations of C S I and C S I PU (see the Appendix section), and for each realization, the corresponding optimum uniform bit and energy allocation and code rate are obtained as described in Section 4.1.
According to these premises and considering that there are active SFs, the resource allocation and the rate adaptation problem that guarantees the different QoS requirements while maximizing the spectral efficiency can be mathematically expressed by. (2).
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