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We study the hybrid classical-quantum version of the channel coding problem for the famous Gel’fand–Pinsker channel. In the classical setting for this channel the conditional distribution of the channel output given the channel input is a function of a random parameter called the channel state. We study this problem when a rate limited version of the channel state is available at the encoder for the classical-quantum Gel’fand–Pinsker channel. We establish the capacity region for this problem in the information-spectrum setting. The capacity region is quantified in terms of spectral-sup classical mutual information rate and spectral-inf quantum mutual information rate. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel relay selection scheme for orthogonal frequency-division multiplexing systems by combining conventional bulk and per-subcarrier selection schemes and analyze its outage performance over equally spatially correlated channels. Specifically, the combined selection scheme selects only two relays at the first attempt and performs per-subcarrier selection over these two relays. We analyze the asymptotic outage performance of the combined selection scheme in the high signal-to-noise ratio (SNR) region and prove a generalized theorem. This theorem states that the combined selection can achieve an optimal outage probability equivalent to the per-subcarrier selection at a high SNR without using the full set of available relays for selection. This unique property is termed the equivalence principle, and it holds for all correlation conditions. To explore this principle, we consider three examples: decode-and-forward, fixed-gain amplify-and-forward (AF), and variable-gain AF relay systems. Furthermore, two extended applications, i.e., antenna selection and branch selection, are also considered to reveal the feasibility and the expandability of the equivalence principle. Our analysis is verified by Monte Carlo simulations. The proposed combined selection and the proved theorem provide a general and feasible solution to the tradeoff between system complexity and outage performance when relay selection is applied. [ABSTRACT FROM AUTHOR]

Throughout the years, measuring the complexity of networks and graphs has been of great interest to scientists. The Kolmogorov complexity is known as one of the most important tools to measure the complexity of an object. We formalized a method to calculate an upper bound for the Kolmogorov complexity of graphs and networks. Firstly, the most simple graphs possible, those with O (1) Kolmogorov complexity, were identified. These graphs were then used to develop a method to estimate the complexity of a given graph. The proposed method utilizes the simple structures within a graph to capture its non-randomness. This method is able to capture features that make a network closer to the more non-random end of the spectrum. The resulting algorithm takes a graph as an input and outputs an upper bound to its Kolmogorov complexity. This could be applicable in, for example evaluating the performances of graph compression methods. [ABSTRACT FROM AUTHOR]

In this paper, an efficient algorithm for selecting a route in a multihop amplify-and-forward (AF) relay network is presented. In particular, a route selection strategy that minimizes the outage probability of the network is proposed. By providing a recursive method to calculate the outage probability, we demonstrate how the algorithm can be implemented based on a dynamic programming approach wherein the relays compute and compare path metrics on a hop-by-hop basis. Simulation results are provided to verify the performance and efficiency of the proposed method relative to other existing approaches. [ABSTRACT FROM PUBLISHER]

Using mutually shift-orthogonal spreading codes, block-spread code-division multiple access (BS-CDMA) systems have been shown to achieve multiuser interference (MUI)-free reception when synchronization between the base station and the subscriber stations is achieved. In practice, when carrier frequency offset (CFO) is present, orthogonality among users is destroyed, and MUI occurs. This paper presents three methods of designing the spreading and despreading codes for uplink BS-CDMA systems to reduce MUI due to CFO. We show through rigorous derivation that all three codes can completely eliminate MUI due to CFO. In particular, by fixing the spreading codes at the transmitter, despreading codes that were obtained by minimizing the interference power or their cross correlation with the spreading codes are shown to yield a performance close to a synchronous system. The advantages and disadvantages of the BS-CDMA systems using the three proposed codes are discussed. [ABSTRACT FROM PUBLISHER]

A novel block-spread code-division multiple access (BS-CDMA) framework is presented whereby user-specific, channel-independent precoding is employed along with special spreading codes to ensure multi-user interference free reception with maximum user load. This framework is presented in a general form, from which other BS-CDMA techniques can be derived. Finally, it is shown that specific precoder and spreading code designs facilitate low-complexity frequency-domain equalization at the receiver. [ABSTRACT FROM AUTHOR]

The age of information (AoI) has been widely used to quantify the information freshness in real-time status update systems. As the AoI is independent of the inherent property of the source data and the context, we introduce a mutual information-based value of information (VoI) framework for hidden Markov models. In this paper, we investigate the VoI and its relationship to the AoI for a noisy Ornstein–Uhlenbeck (OU) process. We explore the effects of correlation and noise on their relationship, and find logarithmic, exponential and linear dependencies between the two in three different regimes. This gives the formal justification for the selection of non-linear AoI functions previously reported in other works. Moreover, we study the statistical properties of the VoI in the example of a queue model, deriving its distribution functions and moments. The lower and upper bounds of the average VoI are also analysed, which can be used for the design and optimisation of freshness-aware networks. Numerical results are presented and further show that, compared with the traditional linear age and some basic non-linear age functions, the proposed VoI framework is more general and suitable for various contexts. [ABSTRACT FROM AUTHOR]

In this paper, a general framework is formalised to characterise the value of information (VoI) in hidden Markov models. Specifically, the VoI is defined as the mutual information between the current, unobserved status at the source and a sequence of observed measurements at the receiver, which can be interpreted as the reduction in the uncertainty of the current status given that we have noisy past observations of a hidden Markov process. We explore the VoI in the context of the noisy Ornstein-Uhlenbeck process and derive its closed-form expressions. Moreover, we investigate the effect of different sampling policies on VoI, deriving simplified expressions in different noise regimes and analysing statistical properties of the VoI in the worst case. We also study the optimal sampling policy to maximise the average information value under the sampling rate constraint. In simulations, the validity of theoretical results is verified, and the performance of VoI in Markov and hidden Markov models is also analysed. Numerical results further illustrate that the proposed VoI framework can support timely transmission in status update systems, and it can also capture the correlation properties of the underlying random process and the noise in the transmission environment. [ABSTRACT FROM AUTHOR]