## 1 Introduction  
Recent advances in Information and Communications Technology (ICT) enable the acquisition, transmission and interpretation of different bio-signals, from fixed or mobile locations. This can support better prevention and well-being and provide valuable and prompt diagnostic tools in various application domains, ranging from home care to emergency care, or situations in which a second or a specialist opinion is required before making a clinical decision [1]. Important trends in healthcare include citizen mobility and the consequent shift towards shared or integrated care where the single doctor-patient relationship has evolved to one in which each individual's healthcare is the responsibility of a team of professionals in a geographically extended healthcare system. In such a new setting, the possibility of collecting clinical information from different points is becoming a common need for citizens and physicians. In this perspective, with focus to the provision of high quality of care, assuring life independency, personalized medicine, the significant new research challenge is the integration of multiple biomedical sensor streams, to extract local and global health-state indicator variables that can be queried and monitored in an unobtrusive way [2]. Wireless biomedical networks serve as the transport mechanism among devices or between devices and traditional backbone networks allowing the transmission of health related information [3]. In this type of networking environment wireless sensing and communication technologies are used to allow acquisition of various bio-signals for subsequent monitoring and analysis [4]. Biomedical body/personal wireless sensor networks have been extensively applied in remote health monitoring and patient care [5,6] allowing wireless, wearable or implanted vital sign sensors to be continuously sampled, such as EEG [7], ECG, SpO2, weight, blood pressure, heart rate[8], _etc._ Although such kinds of networks share many similar properties with general-purpose wireless networks, many domain specific challenges (related to _power consumption_, _transmission range_, _high degree of reliability_, _security_, _etc._) have emerged with respect to specific application domain requirements [9]. A review of applications in healthcare that use wireless biomedical networks and related issues and challenges including interference effect on the network performance is presented in [10]. Today, wireless biomedical communication technologies empower the development of new applications and services to improve the quality of medical care provided to the citizens through ubiquitous healthcare environments [5,6,11,12] raising two crucial issues: (a) RF transmissions can cause electromagnetic interference among biomedical devices, which could as a result critically malfunction or conclude with unsuccessful transmission [13] and (b) different types of electronic health (e-Health) applications and services require different quality of service support [14,15]. It is thus evident that current advances in wireless communication technologies are transforming the delivery of health care. The emphasis is towards personalized and pervasive mobile monitoring focusing on the development of innovative health services to empower individuals in well-being and disease prevention, as well as chronic disease management [16]. These services use a wide range of wireless medical devices and sensors and wireless telecommunication infrastructures to allow ubiquitous remote biomedical monitoring [17; 18; 19; 20]. The objective of this work is to present an in-depth analysis of how cross layer techniques can be used in the design and study of wireless biomedical networks. More specifically, we study how, by adapting various parameters of the telecommunication system, we can: (i) allow more concurrent transmissions; (ii) minimize interference; (iii) enhance network throughput; (iv) maximize individual link data rates; and (v) optimally utilize network resources for all competing transmissions.