Nestor D. Chatzidiamantis

Stylianos E. Trevlakis, Alexandros-Apostolos A. Boulogeorgos, Nestor D. Chatzidiamantis

Optical wireless communications (OWCs) have been recognized as a candidate enabler of next generation in-body nano-scale networks and implants. The development of an accurate channel model capable of accommodating the particularities of different type of tissues is expected to boost the design of optimized communication protocols for such applications. Motivated by this, this paper focuses on presenting a general pathloss model for in-body OWCs. In particular, we use experimental measurements in order to extract analytical expressions for the absorption coefficients of the five main tissues' constitutions, namely oxygenated and de-oxygenated blood, water, fat, and melanin. Building upon these expressions, we derive a general formula for the absorption coefficient evaluation of any biological tissue. To verify the validity of this formula, we compute the absorption coefficient of complex tissues and compare them against respective experimental results reported by independent research works. Interestingly, we observe that the analytical formula has high accuracy and is capable of modeling the pathloss and, therefore, the penetration depth in complex tissues.

Nestor Chatzidiamantis, Evangelia Matskani, Leonidas Georgiadis et al.

In cognitive radio networks, secondary users (SUs) may cooperate with the primary user (PU), so that the success probability of PU transmissions are improved, while SUs obtain more transmission opportunities. Thus, SUs have to take intelligent decisions on whether to cooperate or not and with what power level, in order to maximize their throughput subject to average power constraints. Cooperation policies in this framework require the solution of a constrained Markov decision problem with infinite state space. In our work, we restrict attention to the class of stationary policies that take randomized decisions in every time slot based only on spectrum sensing. The proposed class of policies is shown to achieve the same set of SU rates as the more general policies, and enlarge the stability region of PU queue. Moreover, algorithms for the distributed calculation of the set of probabilities used by the proposed class of policies are presented.