**Author details**

Huanan Yu and Shuxu Guo\* *College of Electronic Science and Engineering, Jilin University, Changchun, China* 

<sup>\*</sup> Corresponding Author

#### **7. References**

82 Ultra Wideband – Current Status and Future Trends

In this chapter, we proposed a pre-filtering method for UWB channel estimation based on the theory of CS, whose measurement matrix is just a Toeplitz matrix, and the channel estimation accuracy is improved. The method proposed in this paper avoided the magnification to the noise. Thus when the reconstructed signal is used as a referent template

The correlation detector for UWB communication discussed in this paper employs the channel estimates to the conventional correlation detection directly, while the design of the whole system combining the channel estimation and signals detection will be a further research. Moreover, it is the key point of improving the BER performance of the correlation detector to search for a CS reconstruction method, which can successfully recover the referent template under the noise realization and fewer measurements with overwhelming probability. In addition, we analyze the choices of reconstruction algorithms using several simulations. Both the OMP and the BPDN algorithms are compared to the Dantzig selector for different signal

Admittedly, there are several other theoretical and practical aspects of UWB channel estimation methods based on compressed sensing that need discussing in future. Below, however, we briefly comment on some of these aspects. First, the different types of measurement matrix according to the UWB channels should be in further study. In this paper, we do some attempts to construct the quasi-Toeplitz matrix developing the model of UWB channel estimator. Somewhat similar theoretical arguments can be made to argue the other type of measurement matrix to get better estimation performance. Second, extensive numerical simulations carried out in literatures for a number of CS estimators have established that the performance of CS estimation methods is markedly superior to that of traditional methods based on LS criterion. However, the nontraditional methods based on MUSIC and ESPRIT algorithms are not optimal for estimating sparse channels. This is because it is possible for a channel to have a small number of resolvable paths but still have a very large number of underlying physical paths, especially in the case of diffuse scattering. So the two algorithms can be employed combining with the compressed sensing framework. Third, one expects the representation of real-world multipath channels in certain bases to be only effectively sparse. The channel model and channel parameters are localized with the perfect channel model in this paper. Finally, and perhaps most importantly for the success of the envisioned wireless systems, the CS can be leveraged to design efficient overcomplete

at the receiver in the noise realization, a better BER performance can be achieved.

noise ratio to give the opinions for choosing suitable reconstruction algorithms.

*College of Electronic Science and Engineering, Jilin University, Changchun, China* 

dictionary for estimating sparse UWB channels.

**Author details** 

Corresponding Author

 \*

Huanan Yu and Shuxu Guo\*

**6. Conclusion** 


Reed J. H.(2005) An introduction to ultra wideband communication systems. *Ser. Prentice Hall Communications Engineering and emerging technologies series, T. S. Tappaport, Ed. Upper Saddle Tiver, NJ: Prentice-Hall,* 2005.

**Chapter 5** 

© 2012 Pomalaza-Ráez and Taparugssanagorn, licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is

© 2012 Pomalaza-Ráez and Taparugssanagorn, licensee InTech. This is a paper distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

properly cited.

**The UWB Channel in Medical Wireless Body** 

UWB is a technology that has several advantages when considered for a Wireless Body Area Network (WBAN). A WBAN is a network with its communications devices in very close proximity to the human body. In medical applications these devices are connected to sensors that can monitor vital signs such as ECG, temperature, and mobility. A WBAN allows for the remote monitoring of a patient's health minimizing the number of cables needed. The monitoring of vital signals usually require a relatively low data-rate which in the case of UWB translates into very small transmitting power, long battery life, and less potential side effects caused by electromagnetic radiation. All of these features are very desirable for devices that are close to the body and meant to be used for extended periods

The human body is a complex structure and human tissues have different electrical properties which affect the propagation of electromagnetic signals. Moreover, as the human body moves, the characteristics of the radio links changes, e.g. the link from the chest to a

To be able to design and develop UWB devices that can interface with WBANs it is then necessary to understand well the characteristics of the radio propagation channel at UWB frequencies and in close proximity to the human body. UWB measurements around a human body have been carried out by several researchers (Fort et al., 2006). There is however a lack of measurements, and subsequent analysis, carried out in real medical environment such as hospitals. The studies described in this chapter focus on scenarios most likely to be found in medical applications and as such they do not assume a large amount of antennas in close proximity to the skin. Among the several issues taken into account are the

wrist will change from line-of-sight to non-line-of-sight as a person walks.

effects of mobility, and the interaction of the UWB signal with medical implants.

Carlos Pomalaza-Ráez and Attaphongse Taparugssanagorn

**Area Networks (WBANs)** 

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/48634

**1. Introduction** 

of time.

