Communication channel

About: Communication channel is a research topic. Over the lifetime, 137411 publications have been published within this topic receiving 1715077 citations. The topic is also known as: communication channel & communications channel.

Performance Comparison of MIMO Techniques for Optical Wireless Communications in Indoor Environments

Abstract: In this paper, we compare the performance of multiple-input-multiple-output (MIMO) techniques applied to indoor optical wireless communications (OWC) assuming line-ofsight (LOS) channel conditions Specifically, several 4 × 4 setups with different transmitter spacings and different positions of the receiver array are considered The following MIMO algorithms are considered: Repetition Coding (RC), Spatial Multiplexing (SMP) and Spatial Modulation (SM) Particularly, we develop a framework to analytically approximate the bit error ratios (BERs) of these schemes and verify the theoretical bounds by simulations The results show that due to diversity gains, RC is robust to various transmitter-receiver alignments However, as RC does not provide spatial multiplexing gains, it requires large signal constellation sizes to enable high spectral efficiencies In contrast, SMP enables high data rates by exploiting multiplexing gains In order to provide these gains, SMP needs sufficiently low channel correlation SM is a combined MIMO and digital modulation technique We show that SM is more robust to high channel correlation compared to SMP, while enabling larger spectral efficiency compared to RC Moreover, we investigate the effect of induced power imbalance between the multiple transmitters It is found that power imbalance can substantially improve the performance of both SMP and SM as it reduces channel correlation In this context, we also show that blocking some of the links is an acceptable method to reduce channel correlation Even though the blocking diminishes the received energy, it outweighs this degradation by providing improved channel conditions for SMP and SM For example, blocking 4 of the 16 links of the 4 × 4 setup improves the BER performance of SMP by more than 20 dB, while the effective signal to noise ratio (SNR) is reduced by about 2 dB due to the blocking Therefore, MIMO techniques can provide gains even under LOS conditions which provide only little channel differences

Cooperative communications with relay-selection: when to cooperate and whom to cooperate with?

Abstract: In this paper; we propose a new cooperative communication protocol, which achieves higher bandwidth efficiency while guaranteeing the same diversity order as that of the conventional cooperative schemes. The proposed scheme considers relay selection via the available partial channel state information (CSI) at the source and the relays. In particular, we discuss the multi-node decode-and-forward cooperative scenarios, where arbitrary N relays are available. The source determines when it needs to cooperate with one relay only, and which relay to cooperate with in case of cooperation, i.e., "When to cooperate?" and "Whom to cooperate with?". An optimal relay is the one which has the maximum instantaneous scaled harmonic mean functionof its source-relay and relay-destination channel gains. For the symmetric scenario, we derive an approximate expression of the bandwidth efficiency and obtain an upper bound on the symbol error rate (SER) performance. We show that full diversity is guaranteed and that a significant increase of the bandwidth efficiency is achieved. Moreover, we present the tradeoff between the achievable bandwidth efficiency and the corresponding SER. Finally, the obtained analytical results are verified through computer simulations.

Application of compressive sensing to sparse channel estimation

Abstract: Compressive sensing is a topic that has recently gained much attention in the applied mathematics and signal processing communities. It has been applied in various areas, such as imaging, radar, speech recognition, and data acquisition. In communications, compressive sensing is largely accepted for sparse channel estimation and its variants. In this article we highlight the fundamental concepts of compressive sensing and give an overview of its application to pilot aided channel estimation. We point out that a popular assumption - that multipath channels are sparse in their equivalent baseband representation - has pitfalls. There are over-complete dictionaries that lead to much sparser channel representations and better estimation performance. As a concrete example, we detail the application of compressive sensing to multicarrier underwater acoustic communications, where the channel features sparse arrivals, each characterized by its distinct delay and Doppler scale factor. To work with practical systems, several modifications need to be made to the compressive sensing framework as the channel estimation error varies with how detailed the channel is modeled, and how data and pilot symbols are mixed in the signal design.

Discrete Memoryless Interference and Broadcast Channels With Confidential Messages: Secrecy Rate Regions

Abstract: We study information-theoretic security for discrete memoryless interference and broadcast channels with independent confidential messages sent to two receivers. Confidential messages are transmitted to their respective receivers while ensuring mutual information-theoretic secrecy. That is, each receiver is kept in total ignorance with respect to the message intended for the other receiver. The secrecy level is measured by the equivocation rate at the eavesdropping receiver. In this paper, we present inner and outer bounds on secrecy capacity regions for these two communication systems. The derived outer bounds have an identical mutual information expression that applies to both channel models. The difference is in the input distributions over which the expression is optimized. The inner bound rate regions are achieved by random binning techniques. For the broadcast channel, a double-binning coding scheme allows for both joint encoding and preserving of confidentiality. Furthermore, we show that, for a special case of the interference channel, referred to as the switch channel, derived bounds meet. Finally, we describe several transmission schemes for Gaussian interference channels and derive their achievable rate regions while ensuring mutual information-theoretic secrecy. An encoding scheme in which transmitters dedicate some of their power to create artificial noise is proposed and shown to outperform both time-sharing and simple multiplexed transmission of the confidential messages.

A physical end-to-end model for molecular communication in nanonetworks

Abstract: Molecular communication is a promising paradigm for nanoscale networks. The end-to-end (including the channel) models developed for classical wireless communication networks need to undergo a profound revision so that they can be applied for nanonetworks. Consequently, there is a need to develop new end-to-end (including the channel) models which can give new insights into the design of these nanoscale networks. The objective of this paper is to introduce a new physical end-to-end (including the channel) model for molecular communication. The new model is investigated by means of three modules, i.e., the transmitter, the signal propagation and the receiver. Each module is related to a specific process involving particle exchanges, namely, particle emission, particle diffusion and particle reception. The particle emission process involves the increase or decrease of the particle concentration rate in the environment according to a modulating input signal. The particle diffusion provides the propagation of particles from the transmitter to the receiver by means of the physics laws underlying particle diffusion in the space. The particle reception process is identified by the sensing of the particle concentration value at the receiver location. Numerical results are provided for three modules, as well as for the overall end-to-end model, in terms of normalized gain and delay as functions of the input frequency and of the transmission range.