# MIMO Channel Estimation in an SDR Platform for Evaluation of D&F Relay Nodes
## 1 Introduction  
Wireless communications services have expanded beyond person-to-person communication. New applications and services have experienced continually increasing demand. Mobile social networking has driven a high content demand, as more profile updates, pictures, and videos of day-to-day activities are uploaded to the World Wide Web. At the same time, streaming video is expected to be the number one driver of mobile traffic. The transition to more experiential activities will place higher demand on networks, requiring greater bandwidth and lower latency, as well as devices with low cost and power consumption [1]. These devices must co-operate to transmit data to the desired location. Relay Nodes (RNs) are a \"relaying technology\" introduced within the LTE (Long-Term Evolution) paradigm, which are commonly preferred due to their high and rapid exchange rate, range, and reliability [2, 3]. Furthermore, they have the ability to overcome multi-path fading and provide diversity gain [4]. On the other hand, various typesof RNs have been proposed in the literature [5] and standardized by organizations such as the 3 GPP [4]. The most common strategies proposed are the Amplify-and-Forward (A&F) and Decode-and-Forward (D&F) protocols [5,6]. The D&F relaying technique decodes, re-modulates, and re-transmits the received signal; however, the A&F protocol only amplifies and re-transmits the signal without any additional processing. Therefore, the D&F strategy is more capable when the channel quality of the source-to-relay link is not sufficient. On the other hand, compared to the A&F protocol, the complexity of the D&F scheme is appreciably higher, due to its greater processing capability. Nevertheless, the re-transmitted signal under the A&F strategy spreads introduced noise, thus degrading the signal received at the destination [7,8]. Studies have been carried out to exploit relay nodes using Multiple-Input and Multiple-Output (MIMO), which implies a technological breakthrough to achieve system performance requirements and cell-edge user throughput. Combining the related technologies with Orthogonal Frequency Division Multiplexing (OFDM) modulation results in communication systems with higher spectral efficiency and less Inter-Symbol Interference (ISI) [9,10]. Most of the existing works have investigated the performance of relay nodes either theoretically or by simulation. It has been widely accepted that simulations often fail to faithfully capture many real-word radio signal propagation effects, which can be overcome by developing physical wireless testbeds. Despite these merits, MIMO-OFDM RN systems still have many unsolved problems, such as the degradation of the signal from the source to the relay node due to the propagation channel, which is then spread to the destination in the second hop. In [11,12], MIMO-OFDM RN schemes were discussed, the Channel State Information (CSI) of which is needed to design the optimal linear receiver. Channel estimation can be utilized to increase the capacity of Orthogonal Frequency Division Multiple Access (OFDMA) systems. At present, accurate channel estimation is a determinant to improve the system performance in terms of capacity, the Bit Error Rate (BER), and other parameters employed to measure the quality of the system. Many channel estimation algorithms can be found in the literature, but they have not been evaluated in the real scenarios of 3 GPP LTE systems. In this paper, we consider the Least-Squares (LS) technique to estimate the pilot symbols in the received signal and implement three interpolators to obtain the data symbols in the received Resource Grid (RG). The Mean Minimum Square Error (MMSE) and Zero-Forcing (ZF) equalizers are also evaluated, prior to processing the signal in the developed relay node. At present, there exist several platforms for testbed evaluation which are suitable to examine the efficiency of RNs. Some platforms are based on Digital Signal Processors (DSPs) or Field Programmable Gate Arrays (FPGAs) [13].