The κ− μ / Inverse Gamma Fading Model

Statistical distributions have been extensively used in modeling fading effects in conventional and modern wireless communications. In the present work, we propose a novel κ − µ composite shadowed fading model, which is based on the valid assumption that the mean signal power follows the inverse gamma distribution instead of the lognormal or commonly used gamma distributions. This distribution has a simple relationship with the gamma distribution, but most importantly, its semi heavy-tailed characteristics constitute it suitable for applications relating to modeling of shadowed fading. Furthermore, the derived probability density function of the κ − µ / inverse gamma composite distribution admits a rather simple algebraic representation that renders it convenient to handle both analytically and numerically. The validity and utility of this fading model are demonstrated by means of modeling the fading effects encountered in body centric communications channels, which have been known to be susceptible to the shadowing effect. To this end, extensive comparisons are provided between theoretical and respective real-time measurement results. It is shown that these comparisons exhibit accurate fitting of the new model for various measurement set ups that correspond to realistic communication scenarios.

The η − µ / Inverse Gamma Composite Fading Model

In this paper we propose a new composite fadingmodel which assumes that the mean signal power of an η−µ signalenvelope follows an inverse gamma distribution. The inversegamma distribution has a simple relationship with the gammadistribution and can be used to model shadowed fading due to itssemi heavy-tailed characteristics. To demonstrate the utility of thenew η−µ / inverse gamma composite fading model, we investigatethe characteristics of the shadowed fading behavior observed inbody centric communications channels which are known to besusceptible to shadowing effects, particularly generated by thehuman body. It is shown that the η−µ / inverse gamma compositefading model provided an excellent fit to the measurement data.Moreover, using Kullback-Leibler divergence, the η −µ / inversegamma composite fading model was found to provide a better fitto the measured data than the κ − µ / inverse gamma compositefading model, for the communication scenarios considered here.

An investigation of IAQ, thermal comfort and Sick Building Syndrome symptoms in UK energy efficient homes

Purpose
– Concern of the deterioration of indoor environmental quality as a result of energy efficient building design strategies is growing. Apprehensions of the effect of airtight, super insulated envelopes, the reduction of infiltration, and the reliance on mechanical systems to provide adequate ventilation (air supply) is promoting emerging new research in this field. The purpose of this paper is to present the results of an indoor air quality (IAQ) and thermal comfort investigation in UK energy efficient homes, through a case study investigation.

Design/methodology/approach
– The case study dwellings consisted of a row of six new-build homes which utilize mechanical ventilation with heat recovery (MVHR) systems, are built to an average airtightness of 2m3/m2/hr at 50 Pascal’s, and constructed without a central heating system. Physical IAQ measurements and occupant interviews were conducted during the summer and winter months over a 24-hour period, to gain information on occupant activities, perception of the interior environment, building-related health and building use.

Findings
– The results suggest inadequate IAQ and perceived thermal comfort, insufficient use of purge ventilation, presence of fungal growth, significant variances in heating patterns, occurrence of sick building syndrome symptoms and issues with the MVHR system.

Practical implications
– The findings will provide relevant data on the applicability of airtight, mechanically ventilated homes in a UK climate, with particular reference to IAQ.

Originality/value
– IAQ data of this nature is essentially lacking, particularly in the UK context. The findings will aid the development of effective sustainable design strategies that are appropriate to localized climatic conditions and sensitive to the health of building occupants.

A Low Complexity Detector with MRC Diversity Reception for MCIK-OFDM

Multi-carrier index keying (MCIK) is a recently developed transmission technique that exploits the sub-carrier indices as an additional degree of freedom for data transmission. This paper investigates the performance of a low complexity detection scheme with diversity reception for MCIK with orthogonal frequency division multiplexing (OFDM). For the performance evaluation, an exact and an approximate closed form expression for the pairwise error probability (PEP) of a greedy detector (GD) with maximal ratio combining (MRC) is derived. The presented results show that the performance of the GD is significantly improved when MRC diversity is employed. The proposed hybrid scheme is found to outperform maximum likelihood (ML) detection with a substantial reduction on the associated computational complexity.

An empirical polarization domain channel availability model for cognitive radio

In dynamic spectrum access networks, cognitive radio terminals monitor their spectral environment in order to detect and opportunistically access unoccupied frequency channels. The overall performance of such networks depends on the spectrum occupancy or availability patterns. Accurate knowledge on the channel availability enables optimum performance of such networks in terms of spectrum and energy efficiency. This work proposes a novel probabilistic channel availability model that can describe the channel availability in different polarizations for mobile cognitive radio terminals that are likely to change their orientation during their operation. A Gaussian approximation is used to model the empirical occupancy data that was obtained through a measurement campaign in the cellular frequency bands within a realistic operational scenario.

An HMM-based spectrum occupancy predictor for energy efficient cognitive radio

Spectrum sensing is the cornerstone of cognitive radio technology and refers to the process of obtaining awareness of the radio spectrum usage in order to detect the presence of other users. Spectrum sensing algorithms consume considerable energy and time. Prediction methods for inferring the channel occupancy of future time instants have been proposed as a means of improving performance in terms of energy and time consumption. This paper studies the performance of a hidden Markov model (HMM) spectrum occupancy predictor as well as the improvement in sensing energy and time consumption based on real occupancy data obtained in the 2.4GHz ISM band. Experimental results show that the HMM-based occupancy predictor outperforms a kth order Markov and a 1-nearest neighbour (1NN) predictor. Our study also suggests that by employing such a predictive scheme in spectrum sensing, an improvement of up to 66% can be achieved in the required sensing energy and time.

Thermal environments and comfort in dementia friendly dwellings

This study follows on from a research project that developed guidelines for the Universal Design (UD) of Dementia Friendly Dwellings for People with Dementia, their Families and Carers. Research findings point to the need for thermal environments that support people with dementia and do not provoke stress, agitation or anxiety. Using semi-structured interviews and qualitative analysis of people with dementia this paper aims to provide insight into the questions of appropriate thermal environments. The qualitative analysis is supported by example simulated indoor environment studies that investigate comfort in common thermal environment provision scenarios in the homes of people with dementia. This paper focuses on the thermal environment, its impact on people with dementia, its therapeutic value, and its role in encouraging engagement in every day activity.
Findings from the interviews emphasize that control over their own internal environment is a priority for people with dementia. A strong preference for naturally or passively conditioned environments over mechanical conditioning is evident. Preferences are expressed for naturally ventilated environments enabling occupant instigated air movement. Repeated emphasis is placed on familiar elements including the fire and hot water bottle. Little desire is expressed for information feedback or technological displays.