No abstract

In this paper, we propose an information geometry approach (IGA) for signal detection (SD) in ultra-massive multiple-input multiple-output (MIMO) systems. We formulate the signal detection as obtaining the marginals of the a posteriori probability distribution of the transmitted symbol vector. Then, a maximization of the a posteriori marginals (MPM) for signal detection can be performed. With the information geometry theory, we calculate the approximations of the a posteriori marginals. It is formulated as an iterative m-projection process between submanifolds with different constraints. We then apply the central-limit-theorem (CLT) to simplify the calculation of the m-projection since the direct calculation of the m-projection is of exponential-complexity. With the CLT, we obtain an approximate solution of the m-projection, which is asymptotically accurate. Simulation results demonstrate that the proposed IGA-SD emerges as a promising and efficient method to implement the signal detector in ultra-massive MIMO systems.

The wireless physical channel parameters are recently used to provide secret key. However, the key generation usually suffers from the quantization errors due to the noise, which decreases the key agreement ratio (KAR) between authorized users. Most existing approaches achieve high KAR by discarding some channel parameters which may lower the key generation efficiency and therefore lower the encryption strength. In the frequency-division duplex (FDD) systems, the number of reciprocal parameters, such as the multipath angle and delay, is limited. Therefore how to find a quantization method with high KAR and encryption strength is one of the major problems for secret key generation in FDD systems. In this paper, a robust quantization scheme based on grouping and shifting is proposed, in which all the available parameters are used for key generation. In addition, a key mapping method with error correction based on Chinese remainder theorem (CRT) is proposed to further improve the KAR performance. Simulations demonstrate the effectiveness of the proposed method.

Cooperative communications is a promising technique for future high speed wireless communications. These systems may be formulated as virtual multi-input multi-output (MIMO) systems where spatial/cooperetive diversity is a key advantage. However, different from MIMO systems, one of the major challenges for cooperative communications systems is that the cooperative transmissions in cooperative systems may be neither time nor frequency synchronized, since the transmissions are from multiple cooperative nodes at different locations. The existing signal designs for co-located MIMO systems may not be able to collect the cooperative diversity in cooperative communications systems. This paper gives an overview of recent research efforts on combating the time and frequency asynchronism of the cooperative communication network. We focus on the signal designs (or space-time codings/modulations) to achieve full cooperative diversity, and summarize some of the resent distributed space-timing coding and space-frequency coding techniques to combat timing errors and frequency offsets, and in the meantime to achieve full cooperative diversity, in both one-way and two-way cooperative networks.