## 1 Introduction  
At present, mobile communications services are demanding higher data rates, more reliable transmission links, better connectivity, and satisfactory Quality of Service (QoS), as well as solutions to the challenges involved with mobility environments [1]. Several solutions have been proposed in order to improve these functionalities. Among the proposed solutions are the Co-ordinated Multi-Point transmission (CoMP) architecture, Moving Extended Cell (MEC), Carrier Aggregation (CA), and Relaying Technology [2]. The latter has been gaining momentum, as it can enable the efficient utilization of communication resources by permitting nodes to co-operate in information exchange with other, thus enhancing the QoS. In this sense, the use of Relay Nodes (RNs) presents several advantages,such as a reduction in the total transmission power, spread in the network capacity, the elimination of penetration losses in outdoor-to-indoor scenarios, and an increase in network coverage [3; 4]. Accordingly, several system architectures involving Relay Nodes have been proposed in the literature [5; 6; 7], in which a stage of intermediate nodes helps the transmitter to communicate with its receiver by employing a shared radio resource [8; 9; 10]. In this context, it is not surprising that the implementation of cellular networks using RNs has become an area of significant research interest, in both industrial and academic spheres [11; 12]. In addition, 3 GPP has undertaken, in recent years, a major effort to study and standardize Relay Nodes, which has been collected in several releases [13; 14; 15], concluding that the technology is expected to be a key enabler for future 5G networks. Although there is a large body of literature involving theoretical analyzes of the benefits of RNs, there are not many articles regarding the practical implementation of RNs and their viability based on empirical measurements. Currently, there exist several platforms for testbed evaluation which are suitable to examine the efficiency of Relay Nodes [16; 17]. However, SDR (Software Defined Radio)-based platforms have been revealed as the most promising option for the practical implementation and evaluation of networks with relay nodes, due to their high performance and flexibility. Additionally, they provide a more suitable option for the implementation of signal processing, through the development and configuration of the Physical Layer (PHY), Medium Access Control Layer (MAC), and some Radio Link Control (RLC). The authors have developed an SDR platform using the Universal Software Radio Peripheral (USRP) and the Matlab\({}^{\text{TM}}\) software [18; 19]. Different types and classifications of Relay Nodes have been proposed in the literature, as considered in the standardization by 3 GPP [15]. The most straightforward way to classify RNs is by their protocol architecture. In this sense, RNs can be classified into Layer 1 (L1), Layer 2 (L2), and Layer 3 (L3). The Amplify-&-Forward (A&F) protocol fulfils of L1 RN functionalities, which simply amplifies the received signal and forwards it to the destination without performing any additional processing [20]. In this context, A&F is a simple solution and introduces almost no delay. Nevertheless, there isn't an improvement in the Signal-to-Interference-plus-Noise-Ratio (SINR) due to that the noise and interferences are also amplified. On the other hand, a Decode-&-Forward strategy symbolizes a Layer 2 Relay, in which the RF signal from the base station (eNodeB, eNB) firstly is decoded, and before of to be forwarded to the destination source it is again encoded [21]. The disadvantage main of this protocol is the delay to re-transmit the received signal, which is due to demodulation/modulation and decoding/encoding processing. However, the D&F strategy presents a high performance in comparison with the A&F scheme. Both A&F and D&F strategies are considered in this paper.