## 1 Introduction
We present our theoretical analysis and simulation results taking into account the number of interfering nodes, and networking parameters of the underline telecommunication system. We investigate how a medium access mechanism, using cross layer cooperative communication techniques [21], can be used for interference compensation at a receiving node from all other interfering transmissions in range and allow successful reception of the signal of interest and thus improve the overall network performance in a seamless and cooperative way to allow different types of health related services and data to be successfully transferred through the wireless medium. Most state-of-the-art systems deal with interference in one of the following two ways, even though both of them might be sub-optimal, either: (a) orthogonalize the communication links in time or frequency so that they do not interfere with each other at all; or (b) allow communication links to share the same degrees of freedom, but treat each other's interference as adding to the noise floor. The first approach entails an a priori loss of degrees of freedom in both links, no matter how weak the potential interference is. The second approach treats interference as noise, while it actually carries information and has structure that can potentially be exploited in mitigating its effect. These considerations lead to the natural question of what is the best performance one can achieve without making any _a priori_ assumptions on how the common resource is shared. A basic information theory model to study this question is the two-user Gaussian interference channel, where two point-to-point links with additive white Gaussian noise interfere with each other. Recent work on the interference channel [22] has shown the frontiers for the achievable rate regions for a _n_-user interference channel determining the shape and size of the rate regions. The usual assumptions in previous works lies in the fact that interference is considered as additional noise and that the maximum achievable rate depends logarithmically on the Signal to Interference and Noise Ratio (SINR). The exact calculation of the interference in a wireless ad hoc network is a difficult task even when special algorithms are used to share information of power and distances among network nodes. Many known studies try to model and calculate interference levels for a wireless multi-hop _ad hoc_ network, taking into account the number of nodes, density of nodes, radio propagation, predefined position of interfering nodes and the amount of relay traffic [23; 24; 25]. The two-user interference channel stability region has been studied in [26] using stochastic dominance techniques also considering the case that each receiver treats interference as Gaussian noise or by employing successive interference cancelation. The work presented in [27] characterizes the capacity region for the two-user Gaussian interference channel within one bit showing that, treating interference as noise, achieves the sum capacity of the two-user Gaussian interference channel in low-interference. Further studies shows that under specific conditions two strongly interfering communication links with additive white Gaussian noise can achieve rates as high as would be achievable without this interference [28]. In [29] upper and lower capacity order-bounds are derived using the concept of the exclusion region to limit interference caused to the receiver. It is shown that the network capacity decreases when the size of the exclusion region (a region around each receiver such that nodes inside it are not allowed to transmit) increases. In [30], the size of the exclusion region is studied, for which an optimal size that maximizes capacity is suggested and is shown to depend on the density of the network nodes. Our goal, in this work, is to control the amount of interference experienced by receivers and, in certain cases, to enforce concurrent transmissions, in order to maximize network performance by tightly coupling both physical and medium access layers.