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Compressed Channel Sensing in THz communications
THz communications is one of the candidates for the future ultrafast wireless transmission. However, the peculiarities of propagation in the THz band result in a very high frequency-selective channel and a much longer channel impulse response (CIR) compared to that of a wireless microwave channel. Moreover it has been observed that the indoor THz channel is sparse, since most of the channel coefficients are either zero or nearly zero. Conventional linear channel estimation strategies, such as the least squares, are ill-suited to fully exploit the characteristics of the THz channel. In contrast, compressed channel sensing seems to be a good candidate.
The basic principle of this concept is to reconstruct the sparse channel h from a number of measurements: y=Ah, taken by the help of a sensing matrix A. To achieve this goal, the following two main tasks have to be solved.
1. How to find a suitable sensing matrix?
2. What reconstruction algorithm is appropriate and exploits the sparse channel characteristics?
In this research-internship we investigate this by studying how different parameters, like channel length, number of measurements and additional noise influence the channel estimation results. We do also analyze achievable performance bounds. As first approaches the “Dantzig-Selector” according to the work of U. Bajwa et. al (http://ieeexplore.ieee.org/document/5454399/) and the GPSR algorithm according to the work of A. T. Figueiredo et. al (http://ieeexplore.ieee.org/document/4407762/) are studied.
Interference Alignment for SC-FDMA Systems with Widely Linear Filtering (ongoing)
In expectation of a growing interference level in cellular systems in the near future, elaborate interference management techniques are necessary in addition to the traditional interference avoidance approaches employed so far. A first step has been done when Coordinated Multi-Point (CoMP) transmission was introduced in the 4G LTE-A standard, allowing an exchange of information between base stations from neighbouring cells. For the network of the next generation, CoMP will additionally embrace most likely centralized processing and distributed cooperation. This new architecture gives way to more advanced cooperation techniques such as interference alignment. Interference alignment is a technique that recently has attracted attention due to its capability to theoretically increase the sum rate of a network without any bound. This is realized by jointly designing precoding filters for the transmitters such that the interference falls into a reserved subspace at the receiver while leaving the remaining subspace interference-free for the desired user. Although theory shows that a complete and perfect alignment is possible, under real conditions residual interference still will be present due to a low signal-to-noise ratio and a limited number of signaling dimensions. Task of the research internship is to investigate widely linear (WL) filtering at the transmitter and the receiver side to overcome the issue associated with limited number of signaling dimensions. For WL filtering the imaginary and the real part of the filter input are processed seperately and subsequently combined linearly. When additionally applying real-valued transmit symbols, a WL system model results wich has doubled dimensions. This translates into more degrees of freedom for the filter design. As the joint optimization over precoding, receive matrices of the users implies an exhaustive search, a suboptimal approach will be examined. The transceiver design is conducted for the 4G formats single-carrier frequencydivision multiple access (SC-FDMA).