We quantify the impact of channel outdatedness and pilot contamination on the achievable spectral efficiency (SE) of uplink massive multiple input multiple output non-orthogonal multiple access (mMIMO-NOMA) system. Specifically, we compute novel closed-form expressions for achievable SE (i) for both ZF and MR decoders based on outdated channel estimates obtained using pilot sharing-based estimation schemes, namely, Scheme-I and Scheme-S, and (ii) for ZF decoder based on predicted channel obtained using Wiener linear predictor. The analysis accounts for time-variations in channel due to Doppler shift, correlation due to pilot sharing and imperfect successive interference cancellation. We formulate and solve optimization problems for max-min and proportional fairness power control using convex programming. We also study equal and inversion power control strategies. Intriguingly, among equal, inversion and max-min power control under channel aging, the ZF decoder based on Scheme-S (i) gives the highest per-user SE with max-min power control for smaller values of normalized Doppler shift$ (f_{D} T_{S}) $and with inversion power control for larger values of$ f_{D} T_{S}$, and (ii) gives the highest minimum user SE with max-min power control. Proportional fairness provides higher per-user SE than max-min power control while maintaining fairness to a significant extent.

In this article, we comprehensively analyze the performance of a cooperative underwater wireless optical communication (UWOC) system involving three nodes, employing selective decode and forward relaying. Our investigation centers on a binary phase shift keying (BPSK) modulated cooperative UWOC system utilizing subcarrier intensity modulation with direct detection (SIM/DD) at the receiver. We account for the combined influence of attenuation and turbulence on the channel links. Attenuation due to absorption and scattering is modeled using Beer-Lambert’s law, while turbulence-induced fading is represented by the exponential generalized gamma (EGG) distribution. Our analysis delves into the performance of the proposed cooperative UWOC system, evaluating metrics like bit error rate (BER) and outage probability (OP). We consider diverse channel parameters for both fresh and salty water scenarios, incorporating uniform and nonuniform temperatures. The closed-form expressions of BER and upper bound OP are evaluated in terms of Fox’s H-function and corroborated through numerical simulations. Our results demonstrate that at 35-dB signal-to-noise ratio (SNR), the cooperative UWOC system has performed significantly better vis-a-vis direct-link UWOC systems, exhibiting a BER enhancement factor of 21.90 at bubble level (BL) 2.4 liter per minute (LPM) and 3.1 at BL 16.5LPM in salty water under uniform temperature conditions. Furthermore, the results emphasize the detrimental impact of increased turbulence on system performance, which supersedes the influence of water salinity.

A primary and cognitive relay spectrum sharing network is considered. The channels are assumed to be κ - μ shadowed fading with arbitrary fading parameters. We obtained expression for outage probability to analyze the performance under the power constraints on maximum transmit power at secondary user (SU) transmitter and relay, and peak interference power at primary user (PU) receiver. The performance of the cognitive relay network is analyzed for various fading parameters and power constraints, which are validated by Monte-Carlo simulations. It is shown that an outage floor is reached when peak interference power at PU receiver is independent of transmitting power at SU transmitter and relay, which gives insight to design a cognitive relay network in the presence of PU network.

For sensor nodes deployed at small distances, computation energy along with radio energy determines the battery life. We have proposed a system-level design space exploration methodology in [1] for searching an energy-efficient error-correcting code (ECC). This methodology takes into account the computation and the radio energy in an integrated manner. In this paper, we validate this methodology by deploying the Imote2 nodes and measuring energy values under different operating modes, e.g., with and without ECC. In this process, we propose a validation framework and node energy model. Experimental results validate the methodology and show that with ECC we can save up to 14% transmitter energy under a certain set of conditions. The main contribution of this paper is that it establishes experimentally that our methodology is effective in exploration of various node configurations and finding an energy-efficient solution.

For closely deployed sensor nodes, computation energy along with radio energy determines the battery life. We have proposed a system level design space exploration methodology [1] for searching an energy efficient error correcting code (ECC). This methodology takes into account the computation and the radio energy in an integrated manner. In this paper we validate this methodology by deploying Imote2 nodes and measuring energy values under different operating modes, e.g., with and without ECC. Experimental results validate the methodology and show that with ECC we can save upto 13% transmitter energy for certain set of conditions. This paper validates experimentally that our methodology is effective in exploration of various node configurations and finding an energy efficient solution.

In this paper, we first establish that, in wireless sensor networks, operating over ldquosmallrdquo distances, both computation energy and radio energy influence the battery life. In such a scenario, to evaluate the utility of error-correcting codes (ECCs) from an energy perspective, one has to consider the energy consumed in encoding-decoding and transmitting additional ldquoredundantrdquo bits vis-a-vis the energy saved due to coding gain. This paper presents a framework for evaluating various ECCs based on a comprehensive energy model of a sensor node. The framework supports exploration of sensor node design space with application- and deployment-related parameters, like distance, bit error rate, path loss exponent, as well as the modulation scheme and ECC parameters. The exploration results show that, as compared to the uncoded-data transmission, the energy-optimal ECC saves 15%-60% node energy for the given parameters.

Optimizing energy consumption is a key objective in designing wireless sensor nodes. It has been shown earlier that the node energy is strongly influenced by the modulation and the error correcting code (ECC) used. The utility of using ECC from an energy perspective is determined by the energy saving due to the ECC coding gain vis-a-vis the energy overhead of "redundant" bits and of energy saving. Furthermore, the node energy varies with the change in errorcorrecting capability and code word length of a particular ECC as well as the modulation constellation size. The ECC coding gain is influenced by the constellation size. In this paper, the node energy variations with ECC and modulation parameters are analyzed for an energy optimal node design for the nodes operating in the additive white Gaussian noise channel. Based on this analysis, we compute the per information bit node energy and this is used to select an "optimal" ECC and modulation scheme pair. Our results show that the energy optimal ECC-modulation pair selected for some specific operating conditions could save as much as 50% energy. In nutshell, our work is targeted towards reducing the search space and finding an energy optimal ECC modulation pair for the given environment and application.

In wireless sensor networks due to the small transmission distances involved, the computation energy along with the radio energy determines the battery life. Energy consumption of error control codes (ECCs) is a complex function of the energy consumption in computing encoding-decoding, transmitting "redundant" bits and energy saved by coding gain. This paper presents a methodology, which integrates computation and radio energy for searching an energy optimal ECC. Based on this methodology, a design space exploration framework and the energy model of sensor node have been developed. Exploration results show that the energy optimal ECC saves 15-58% node energy for given parameters.