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Hence, Cmax is indeed the maximum channel capacity value.
According to [18], non-linear precoding techniques can approach the maximum channel capacity with high computational complexity.
Fig. 19 Example of a measured LOS 2×2 MIMO-OFDM V2I maximum channel capacity, C max=13.37 bps/Hz, D=76.7 m for the LSS scenario Fig. 20 Example of a measured LOS 2×2 MIMO-OFDM V2I maximum channel capacity, C max≈13.0 bps/Hz, D=13.1 m for the MSS scenario Fig. 21 Example of a measured LOS 2×2 MIMO-OFDM V2I maximum channel capacity, C max=13.57 bps/Hz, D=59 m for the SSS scenario.
Water-filling (WF) algorithm is often used in communication systems to utilize maximum channel capacity when there is a constraint on the available power.
Thus, and taking into account (26), the eigenvalues that allow to achieve the maximum channel capacity are given by γ i, q = n T n R n, ∀ i, q. (32).
This implies that if (9) is met based on the positioning and separation of TX and RX, we will achieve the maximum channel capacity in a 2×2 MIMO system.
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Figures 19, 20, and 21 present the measured maximum MIMO channel capacity for the LSS, MSS, and SSS scenarios, respectively.
Assuming that the video encoder uses the maximum allocated channel capacity, the rate of encoded video can be computed as follows [6]: (4).
For the LSS case, the maximum MIMO channel capacity is 13.37 bps/Hz, followed by 13.17 bps/Hz at separation distances of 76.7 and 15 m and at a relative speeds of 31.7 and 8.8 km/h, respectively.
As a result, there is the optimum number of the relay nodes for maximum end-to-end channel capacity. Figure 8 The end-to-end channel capacity responded to each number of relay node where W is 500 m.
The incremental selection AST (I-AST) adds successively antennas at every stage, so the antenna that yields the maximum increase of the channel capacity is added to the set of P transmit antennas [14].
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