Dual-Branch MRC Receivers under Spatial Interference Correlation and Nakagami Fading

Despite being ubiquitous in practice, the performance of maximal-ratio combining (MRC) in the presence of interference is not well understood. Because the interference received at each antenna originates from the same set of interferers, but partially de-correlates over the fading channel, it possesses a complex correlation structure. This work develops a realistic analytic model that accurately accounts for the interference correlation using stochastic geometry. Modeling interference by a Poisson shot noise process with independent Nakagami fading, we derive the link success probability for dual-branch interference-aware MRC. Using this result, we show that the common assumption that all receive antennas experience equal interference power underestimates the true performance, although this gap rapidly decays with increasing the Nakagami parameter $m_{\text{I}}$ of the interfering links. In contrast, ignoring interference correlation leads to a highly optimistic performance estimate for MRC, especially for large $m_{\text{I}}$. In the low outage probability regime, our success probability expression can be considerably simplified. Observations following from the analysis include: (i) for small path loss exponents, MRC and minimum mean square error combining exhibit similar performance, and (ii) the gains of MRC over selection combining are smaller in the interference-limited case than in the well-studied noise-limited case.Comment: to appear in IEEE Transactions on Communication

Adaptive RRI Selection Algorithms for Improved Cooperative Awareness in Decentralized NR-V2X

Decentralized vehicle-to-everything (V2X) networks (i.e., C-V2X Mode-4 and NR-V2X Mode-2) utilize sensing-based semi-persistent scheduling (SPS) where vehicles sense and reserve suitable radio resources for Basic Safety Message (BSM) transmissions at prespecified periodic intervals termed as Resource Reservation Interval (RRI). Vehicles rely on these received periodic BSMs to localize nearby (transmitting) vehicles and infrastructure, referred to as cooperative awareness. Cooperative awareness enables line of sight and non-line of sight localization, extending a vehicle's sensing and perception range. In this work, we first show that under high vehicle density scenarios, existing SPS (with prespecified RRIs) suffer from poor cooperative awareness, quantified as tracking error. Decentralized vehicle-to-everything (V2X) networks (i.e., C-V2X Mode-4 and NR-V2X Mode-2) utilize sensing-based semi-persistent scheduling (SPS) where vehicles sense and reserve suitable radio resources for Basic Safety Message (BSM) transmissions at prespecified periodic intervals termed as Resource Reservation Interval (RRI). Vehicles rely on these received periodic BSMs to localize nearby (transmitting) vehicles and infrastructure, referred to as cooperative awareness. Cooperative awareness enables line of sight and non-line of sight localization, extending a vehicle's sensing and perception range. In this work, we first show that under high vehicle density scenarios, existing SPS (with prespecified RRIs) suffer from poor cooperative awareness, quantified as tracking error

NTN-based 6G Localization: Vision, Role of LEOs, and Open Problems

Since the introduction of 5G Release 18, non-terrestrial networks (NTNs) based positioning has garnered significant interest due to its numerous applications, including emergency services, lawful intercept, and charging and tariff services. This release considers single low-earth-orbit (LEO) positioning explicitly for $\textit{location verification}$ purposes, which requires a fairly coarse location estimate. To understand the future trajectory of NTN-based localization in 6G, we first provide a comprehensive overview of the evolution of 3rd Generation Partnership Project (3GPP) localization techniques, with specific emphasis on the current activities in 5G related to NTN location verification. We then delineate the suitability of LEOs for location-based services and emphasize increased interest in LEO-based positioning. In order to provide support for more accurate positioning in 6G using LEOs, we identify two NTN positioning systems that are likely study items for 6G: (i) multi-LEO positioning, and (ii) augmenting single-LEO and multi-LEO setups with Global Navigation Satellite System (GNSS), especially when an insufficient number of GNSS satellites (such as 2) are visible. We evaluate the accuracy of both systems through a 3GPP-compliant simulation study using a Cram\'{e}r-Rao lower bound (CRLB) analysis. Our findings suggest that NTN technology has significant potential to provide accurate positioning of UEs in scenarios where GNSS signals may be weak or unavailable, but there are technical challenges in accommodating these solutions in 3GPP. We conclude with a discussion on the research landscape and key open problems related to NTN-based positioning.Comment: 7 pages, 6 figures, submitted to IEEE Wireless Communications Magazin

Development of High-Purity Optical Grade Single-Crystal CVD Diamond for Intracavity Cooling

Microwave assisted chemical vapour deposited bulk diamond products have been used in a range of high power laser systems, due to low absorption across a range of wavelengths and exceptional thermal properties. However the application of polycrystalline products has frequently been limited to applications at longer wavelengths or thermal uses outside of the optical path due to the birefringence and scatter that are intrinsic properties of the polycrystalline materials. However, there are some solid state structures, including thin disc gain modules and amplifiers, that will gain significantly in terms of potential output powers if diamond could be used as a heat spreader in the optical path as well as a heat spreader on the rear surface of the disk. Therefore single crystal grades of diamond have been developed that overcome the limitations of the polycrystalline material, with low absorption, low scatter and low birefringence grades for demanding optical applications. We will present new data, characterising the performance of these materials across infra-red and visible wavelengths with absorption coefficient measured by laser calorimetry at a range of wavelengths from 1064 nm to 452 nm

Canagliflozin and renal outcomes in type 2 diabetes and nephropathy

BACKGROUND Type 2 diabetes mellitus is the leading cause of kidney failure worldwide, but few effective long-term treatments are available. In cardiovascular trials of inhibitors of sodium–glucose cotransporter 2 (SGLT2), exploratory results have suggested that such drugs may improve renal outcomes in patients with type 2 diabetes. METHODS In this double-blind, randomized trial, we assigned patients with type 2 diabetes and albuminuric chronic kidney disease to receive canagliflozin, an oral SGLT2 inhibitor, at a dose of 100 mg daily or placebo. All the patients had an estimated glomerular filtration rate (GFR) of 30 to <90 ml per minute per 1.73 m2 of body-surface area and albuminuria (ratio of albumin [mg] to creatinine [g], >300 to 5000) and were treated with renin–angiotensin system blockade. The primary outcome was a composite of end-stage kidney disease (dialysis, transplantation, or a sustained estimated GFR of <15 ml per minute per 1.73 m2), a doubling of the serum creatinine level, or death from renal or cardiovascular causes. Prespecified secondary outcomes were tested hierarchically. RESULTS The trial was stopped early after a planned interim analysis on the recommendation of the data and safety monitoring committee. At that time, 4401 patients had undergone randomization, with a median follow-up of 2.62 years. The relative risk of the primary outcome was 30% lower in the canagliflozin group than in the placebo group, with event rates of 43.2 and 61.2 per 1000 patient-years, respectively (hazard ratio, 0.70; 95% confidence interval [CI], 0.59 to 0.82; P=0.00001). The relative risk of the renal-specific composite of end-stage kidney disease, a doubling of the creatinine level, or death from renal causes was lower by 34% (hazard ratio, 0.66; 95% CI, 0.53 to 0.81; P<0.001), and the relative risk of end-stage kidney disease was lower by 32% (hazard ratio, 0.68; 95% CI, 0.54 to 0.86; P=0.002). The canagliflozin group also had a lower risk of cardiovascular death, myocardial infarction, or stroke (hazard ratio, 0.80; 95% CI, 0.67 to 0.95; P=0.01) and hospitalization for heart failure (hazard ratio, 0.61; 95% CI, 0.47 to 0.80; P<0.001). There were no significant differences in rates of amputation or fracture. CONCLUSIONS In patients with type 2 diabetes and kidney disease, the risk of kidney failure and cardiovascular events was lower in the canagliflozin group than in the placebo group at a median follow-up of 2.62 years

Adaptive RRI Selection Algorithms for Improved Cooperative Awareness in Decentralized NR-V2X

Decentralized vehicle-to-everything (V2X) networks (i.e., C-V2X Mode-4 and NR-V2X Mode-2) utilize sensing-based semi-persistent scheduling (SPS) where vehicles sense and reserve suitable radio resources for Basic Safety Message (BSM) transmissions at prespecified periodic intervals termed as Resource Reservation Interval (RRI). Vehicles rely on these received periodic BSMs to localize nearby (transmitting) vehicles and infrastructure, referred to as cooperative awareness. Cooperative awareness enables line of sight and non-line of sight localization, extending a vehicle’s sensing and perception range. In this work, we first show that under high vehicle density scenarios, existing SPS (with prespecified RRIs) suffer from poor cooperative awareness, quantified as tracking error. Tracking error is defined as the difference between a vehicle’s true and estimated location as measured by its neighbors. To address the issues of static RRI SPS and improve cooperative awareness, we propose two novel RRI selection algorithms– namely, Channel-aware RRI (Ch-RRI) selection and Age of Information (AoI)-aware RRI (AoI-RRI) selection. Ch-RRI dynamically selects an RRI based on channel resource availability depending upon the (sparse or dense) vehicle densities, whereas AoI-RRI utilizes a novel information freshness metric, called Age of Information (AoI) to select a suitable RRI. Both adaptive RRI algorithms use SPS for selecting transmission opportunities for timely BSM transmissions at the chosen RRI. System-level simulations demonstrate that both proposed schemes outperform the SPS with fixed RRI in terms of improved cooperative awareness. Furthermore, AoI-RRI SPS outperforms Ch-RRI SPS in high densities, whereas Ch-RRI SPS is slightly better than AoI-RRI SPS in low densities