Signal Processing for Compressed Sensing Multiuser Detection

The era of human based communication was longly believed to be the main driver for the development of communication systems. Already nowadays we observe that other types of communication impact the discussions of how future communication system will look like. One emerging technology in this direction is machine to machine (M2M) communication. M2M addresses the communication between autonomous entities without human interaction in mind. A very challenging aspect is the fact that M2M strongly differ from what communication system were designed for. Compared to human based communication, M2M is often characterized by small and sporadic uplink transmissions with limited data-rate constraints. While current communication systems can cope with several 100 transmissions, M2M envisions a massive number of devices that simultaneously communicate to a central base-station. Therefore, future communication systems need to be equipped with novel technologies facilitating the aggregation of massive M2M. The key design challenge lies in the efficient design of medium access technologies that allows for efficient communication with small data packets. Further, novel physical layer aspects have to be considered in order to reliable detect the massive uplink communication. Within this thesis physical layer concepts are introduced for a novel medium access technology tailored to the demands of sporadic M2M. This concept combines advances from the field of sporadic signal processing and communications. The main idea is to exploit the sporadic structure of the M2M traffic to design physical layer algorithms utilizing this side information. This concept considers that the base-station has to jointly detect the activity and the data of the M2M nodes. The whole framework of joint activity and data detection in sporadic M2M is known as Compressed Sensing Multiuser Detection (CS-MUD). This thesis introduces new physical layer concepts for CS-MUD. One important aspect is the question of how the activity detection impacts the data detection. It is shown that activity errors have a fundamentally different impact on the underlying communication system than data errors have. To address this impact, this thesis introduces new algorithms that aim at controlling or even avoiding the activity errors in a system. It is shown that a separate activity and data detection is a possible approach to control activity errors in M2M. This becomes possible by considering the activity detection task in a Bayesian framework based on soft activity information. This concept allows maintaining a constant and predictable activity error rate in a system. Beyond separate activity and data detection, the joint activity and data detection problem is addressed. Here a novel detector based on message passing is introduced. The main driver for this concept is the extrinsic information exchange between different entities being part of a graphical representation of the whole estimation problem. It can be shown that this detector is superior to state-of-the-art concepts for CS-MUD. Besides analyzing the concepts introduced simulatively, this thesis also shows an implementation of CS-MUD on a hardware demonstrator platform using the algorithms developed within this thesis. This implementation validates that the advantages of CS-MUD via over-the-air transmissions and measurements under practical constraints

Project OASIS: The Design of a Signal Detector for the Search for Extraterrestrial Intelligence

An 8 million channel spectrum analyzer (MCSA) was designed the meet to meet the needs of a SETI program. The MCSA puts out a very large data base at very high rates. The development of a device which follows the MCSA, is presented

Evaluation of flexible SPA based LPDC decoder using hardware friendly approximation methods

Due to computation-intensive nature of LDPC decoders, a lot of research is going towards efficient implementation of their original algorithm (SPA). As "Min-Sum" approximation is basically an overestimation of SPA, this thesis investigates more accurate, yet area efficient, approximations of SPA, to select an optimum one. In a general comparison between main approximation methods (e.g. LUT, PWL, CRI), PWL showed the most area-efficiency. Studying different mathematical formats of SPA, Soft-XOR based format with forward-backward scheme was chosen for hard- ware implementation. Its core function (Soft-XOR) was implemented with CRI approximation, which achieved the highest efficiency, compare to other approxi- mations. Using this core function, a flexible, pipe-lined, Soft-XOR based CNU (the computational unit of LDPC decoders) with forward-backward architecture was developed in 18nm CMOS. The implemented CNU’s area and speed can eas- ily be changed in instantiation. A SPA decoder based on the developed CNU was estimated to have an area of 1.6M as equivalent gate count and a throughput of 10Gb/s, with a frequency of 1.25GHz and for 10 iterations. The decoder uses IEEE 802.11n Wi-Fi standard with flooding schedule. The BER/SNR loss, com- pare to floating-point SPA, is 0.3dB for 10 iterations and less than 0.1dB for 20 iterations.You have to get lost before you can be found, a quote by Jeff Rasley goes very well for Low Density Parity Check (LDPC) codes. First invented by Gallager in 1962 but kind of lost during the journey of evolution of telecommunication networks because of their high complexity and demanding computations, which technology was not so advanced to handle, at that time. However, during late 1990s, success of turbo codes invoked the re-discovery of Low Density Parity Check (LDPC) codes. Recently it has attracted tremendous research interest among the scientific com- munity, as today’s technology is advanced enough and to make LDPC decoders completely commercial. In a wireless network, the information is not just sim- ply sent, but first encoded. In a sense, all the transmitted bits are tied together, according to some mathematical rules. Therefore, if noise destructs parts of the information while traveling, the LDPC decoder at the receiver side, can automat- ically detect and retrieve those parts, based on the other parts. Here, our main focus is on the decoder. For actual hardware implementation of the decoder, some level of approximation of the ideal algorithm is always necessary, which reduces the accuracy depending on the approximation. Ericsson is developing the next-generation wireless network for 5G, and already possesses the "Min-Sum" approximation of the LDPC decoder. As the current requirements demand more accurate decoders, the goal of this thesis is to evalu- ate a more accurate but more costly version of the LDPC decoder, as well as its flexibility. Thus, several candidates were selected and evaluated based on their complexity, cost, and their accuracy towards error correction. After performing several trade-offs, an approximation method is chosen and the corresponding cost is derived. With this acquired data, a trade-off between accuracy and cost can be made, depending on the application

Signal design for Multiple-Antenna Systems and Wireless Networks

This dissertation is concerned with the signal design problems for Multiple Input and Multiple Output (MIMO) antenna systems and wireless networks. Three related but distinct problems are considered.The first problem considered is the design of space time codes for MIMO systems in the case when neither the transmitter nor the receiver knows the channel. We present the theoretical concept of communicating over block fading channel using Layered Unitary Space Time Codes (LUSTC), where the input signal is formed as a product of a series of unitary matrices with corresponding dimensionality. We show the channel capacity using isotropically distributed (i.d.) input signaling and optimal decoding can be achieved by layered i.d. signaling scheme along with a low complexity successive decoding. The closed form layered channel capacity is obtained, which serves as a design guideline for practical LUSTC. In the design of LUSTC, a successive design method is applied to leverage the problem of optimizing over lots of parameters.The feedback of channel state information (CSI) to the transmitter in MIMO systems is known to increase the forward channel capacity. A suboptimal power allocation scheme for MIMO systems is then proposed for limited rate feedback of CSI. We find that the capacity loss of this simple scheme is rather small compared to the optimal water-filling solution. This knowledge is applied for the design of the feedback codebook. In the codebook design, a generalized Lloyd algorithm is employed, in which the computation of the centroid is formulated as an optimization problem and solved optimally. Numerical results show that the proposed codebook design outperforms the existing algorithms in the literature.While it is not feasible to deploy multiple antennas in a wireless node due to the space limitation, user cooperation is an alternative to increase performance of the wireless networks. To this end, a coded user cooperation scheme is considered in the dissertation, which is shown to be equivalent to a coding scheme with the encoding done in a distributive manner. Utilizing the coding theoretic bound and simulation results, we show that the coded user cooperation scheme has great advantage over the non-cooperative scheme