In this paper, we propose to use spatial modulation (SM) and the generalized spatial modulation (GSM) MIMO schemes in indoor line-of-sight (LOS) millimeter-wave (mmWave) communication at 60GHz. SM/GSM are known but only at low-GHz frequencies where the channels are typically rich scattered and characterized by Rayleigh or Rician distribution. However, 60-GHz indoor channels are typically not rich but rather sparsely scattered and dominated by the LOS component, thus making them different from low-GHz fading channels and our work novel. We first seek to optimize SM in LOS by finding the channel conditions that minimize its symbol error probability (SEP). Then, we extend our studies to LOS GSM and derive its channel capacity and SEP. Furthermore, we present numerical studies on the behavior and performance of SM/GSM in LOS. LOS spatial multiplexing and beamforming MIMO schemes are used as benchmarks for comparison. At last, we propose novel TX and RX hardware architectures, both of which use only a single RF chain, for implementation of SM/GSM at mmWave frequencies. Both simplicity and good performance are exhibited by LOS SM/GSM thus making them very attractive techniques for short-range indoor mmWave communications at 60GHz.

Cooperative localization in agent networks based on interagent time-of-flight measurements is closely related to synchronization. To leverage this relation, we propose a Bayesian factor graph framework for cooperative simultaneous localization and synchronization (CoSLAS). This framework is suited to mobile agents and time-varying local clock parameters. Building on the CoSLAS factor graph, we develop a distributed (decentralized) belief propagation algorithm for CoSLAS in the practically important case of an affine clock model and asymmetric time stamping. Our algorithm is compatible with real-time operation and a time-varying network connectivity. To achieve high accuracy at reduced complexity and communication cost, the algorithm combines particle implementations with parametric message representations and takes advantage of a conditional independence property. Simulation results demonstrate the good performance of the proposed algorithm in a challenging scenario with time-varying network connectivity.

In this paper, we study the capacity and symbol error probability (SEP) of generalized spatial modulation (GSM) multiple-input multiple-output (MIMO) using measured channels that are obtained by channel sounding in an indoor office environment at 60GHz. Spatial modulation (SM) and GSM are emerging low-complexity MIMO schemes that have been extensively researched for low-GHz (below 6GHz) communications. Recently, they have been considered and shown to be promising also for (mmWave) communications. In the simplest possible case, they require only one RF chain both at the transmitter (TX) and receiver (RX), and thus, are especially attractive for mmWave communications, in which the number of RF chains needs to be as low as possible. Despite of some early works on the theoretical analysis of SM/GSM for mmWave communications, there have been no investigations using real-world channel data. We focus on the office line-of-sight (LOS) scenario and investigate three problems: 1) the performance of GSM using the extracted LOS component of measured channels; 2) the impact of non-LOS NLOS components on the performance of GSM; and 3) possible simple modulation and reception algorithms for GSM that rely only on the LOS component of the channel. The results being reported in this paper not only validate the main claims of previous studies based on ideal pure LOS channels, but also lead to novel findings. One major conclusion is that NLOS components are harmful to the SEP of GSM and should be avoided. As another important outcome, our results strongly motivate the use of precoding in GSM systems to simultaneously improve the channel capacity and reduce the physical size of MIMO arrays (thus eliminating one major issue of LOS GSM).

Synchronization is a key functionality in wireless networks, enabling a wide variety of services. We consider a Bayesian inference framework whereby network nodes can achieve phase and skew synchronization in a fully distributed way. In particular, under the assumption of Gaussian measurement noise, we derive two message passing methods (belief propagation and mean field), analyze their convergence behavior, and perform a qualitative and quantitative comparison with a number of competing algorithms. We also show that both methods can be applied in networks with and without master nodes. Our performance results are complemented by, and compared with, the relevant Bayesian Cramér-Rao bounds.

In this letter, we investigate diffusion-based molecular communication between two mobile nano-machines. We derive a closed-form expression for the first hitting time distribution by characterizing the motion of the information particles and the nano-machines via Brownian motion. We validate the derived expression through a particle-based simulation. For the information transfer we consider single particles of different types, where transposition errors are the dominant source of errors. We derive an analytical expression for the expected bit error probability and evaluate the error performance for the static and the mobile case by means of computer simulations.