Doppler Spectrum

The fading characteristics of the indoor wireless channels are very different from the one we know from the mobile case. In indoor wireless systems transmitter and receiver are stationary and people are moving in between, while in outdoor mobile systems the user terminal is often moving through an environment. As a result, a function

S

( f) has to be defined for indoor environments in order to fit the Doppler power spectrum measurements [12].

S

( f) can be expressed as (in linear values, not dB values):

where

v is the environmental speed determined from measurements that satisfy (6-14),

_o and λ is the wavelength defined by

f

c

=

c

λ

(6-16)

where c is the light speed and

f is the carrier frequency. The value for

_c

v is

_o proposed equal to 1.2 km/h [12].

6.4 Simulated UWB-MIMO Channel Properties Using Matlab Program

In this section we determine some of the important properties of the simulated channel matrices H, specifically channel capacity. For the simulation, we use the following antenna configuration system

• 4 transmit and 4 receive antennas (4x4 UWB-MIMO system)

• Uniform linear array (ULA)

•

λ

/2 adjacent antenna spacing

• Isotropic antennas

• No antenna coupling effect

• All antennas with same polarization (vertical)

Figure 6-1、6-2、6-3、6-4 shows cumulative distribution functions (CDFs) of capacity for Models A-D including measured data, 802.11n channel model and i.i.d. case (channel matrix elements are i.i.d., zero-mean unit-variance complex Gaussian random variables) assuming ρ= 10 dB, 2000 channel realizations, and 4x4 UWB-MIMO system.

Fig.6-1 Computed and measured 4×4 UWB-MIMO capacity CDF for model A and scenario I.

Fig.6-2 Computed and measured 4×4 UWB-MIMO capacity CDF for model B and scenario II.

Fig.6-3 Computed and measured 4×4 UWB-MIMO capacity CDF for model C and scenario III.

Fig.6-4 Computed and measured 4×4 UWB-MIMO capacity CDF for model D and scenario IV.

Table 9 Capacity of our simulated model, 802.11n channel model and measured

Table 9 shows mean capacity and STD of our UWB-MIMO channel model, 802.11n channel model and measured results for each model.

From table 9 we can see that our computed results match very well with measured results. For the models B and D it is expected that capacity is higher because of the more clusters present with wider AS when compared to the models A and C.

Chapter 7

Conclusion

In this thesis, capacity, EDOF and correlations have been measured to analyze the effects of propagation, array arrangement and bandwidth on a 4x4 UWB-MIMO system.

The array arrangement includes antenna array spacing and array orientation. Six propagation scenarios are included to give a complete study of the effects. The measurement using Agilent 8719ET vector network analyzer was carried out in the National Chiao Tung University campus.

We develop indoor UWB-MIMO channel model. We first present the characterization of UWB channels for indoor environment with our measurements. Then we base on 802.11n channel model to modify and combing UWB channel model to develop UWB-MIMO channel model. Finally, we verify our channel model with our measured data.

In this research, some phenomena are observed and listed as following:

(1) Propagation distance effect: The UWB-MIMO capacity is dependent of Tx-Rx distance in LOS with light clutter, i.e. capacity is lower when Tx-Rx distance in small AS (Angular Spread) of AOA/AOD. And capacity is independent of Tx-Rx distance in the environment with heavy clutter, i.e. capacity is similar for any Tx-Rx distance when AS of AOA/AOD is large. It is reported in the literature [16] that in a “wave guiding”

environment the capacity decreases as the Tx-Rx distance increases. In this thesis, we choose four paths in the lobby and laboratory representing LOS/NLOS with light/heavy clutter (scenarios I/II/III/IV) but different from the environment in [16]. Our result is

different from [16]. This is because long distance in the hall the dominant signal component will be the LOS component and the angular spread is limited, thus substantially increases the correlations and results in lower capacity in the literature [16]

but not the condition in our measurement sites.

(2) Local scatterers effect: local scatterers around tx/rx array will affect the capacity, i.e. enhance UWB-MIMO performance. This is because the local scatterers reflect more multipath and more multipath result in low correlation coefficient and then obtain higher capacity.

(3) Antenna spacing effect: measurement results in this thesis show that antenna spacing may affect UWB-MIMO capacity and correlations under any environment (scenarios I/II/III/IV). Furthermore the UWB-MIMO capacity increases as the antenna spacing increases and it saturates when the spacing is larger than 0.5λ . This reveals that the correlation distance between the elements in indoor environments is about 0.5λ .

(4) Antenna array orientation effect: in a ‘wave guiding’ environment such as a long corridor (scenarios V/VI), a significant difference in capacity is observed when the linear receiver array orientation is changed from parallel to perpendicular (to the LOS). In a

‘non wave guiding’ environment such as laboratory (scenarios II/IV), there is no remarkable discrepancy between results of different orientations.

(5) Capacity Loss: for a more in-depth analysis of the performance of UWB-MIMO systems, measurements were done to investigate the effects of SNR and antenna correlation on UWB-MIMO channel capacity. For small antenna spacing, when SNR increases, the channel capacity loss increases initially but decreases gradually afterwards.

It means that in small antenna spacing, the relative channel capacity loss due to the effect of high antenna correlation is reduced as SNR increases. In other words the UWB-MIMO system is robust against the high antenna correlation when SNR is high.

When Tx-Rx distance is in near distance, although antenna correlation is high but if received SNR is excess 10dB then the UWB-MIMO system is robust against the antenna correlation. From above results, we find that the loss of channel capacity owing to high correlation is significantly reduced when the SNR is sufficiently high.

(6) Bandwidth effect: our results show a small difference in capacity when using the larger bandwidth. Hence not much frequency diversity is available.

(7) UWB channel model: from the parameter of S-V model in UWB radio channel model, we can see that Γ decay faster in the LOS condition than in the NLOS condition.

From [19] we can see that in the broadband system, Γ、γ have different decay slope, but we find that in the UWB system Γ、γ have similar decay slope from our measured results.

(8) UWB MIMO channel model: the UWB-MIMO channel model has been proved to be effective and accurate.

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在文檔中 超寬頻多輸入多輸出系統模型之建構與量測 (頁 79-0)