Memory optimization of MAP turbo decoder algorithms

Turbo codes are the most recent breakthrough in coding theory. However, the decoder's implementation cost limits their incorporation in commercial systems. Although the decoding algorithm is highly data dominated, no true memory optimization study has been performed yet. We have extensively and systematically investigated different memory optimizations for the maximum a posteriori (MAP) class of decoding algorithms. It turns out that it is not possible to present one decoder structure as being optimal. In fact, there are several tradeoffs, which depend on the specific turbo code, the implementation target (hardware or software), and the selected cost function. We therefore end up with a parametric family of new optimized algorithms out of which the designer can choose. The impact of our optimizations is illustrated by a representative example, which shows a significant decrease in both decoding energy (factor 2.5) and delay (factor 1.7)     

Nanoencapsulation of Gla-Rich Protein (GRP) as a Novel Approach to Target Inflammation

Chronic inflammation is a major driver of chronic inflammatory diseases (CIDs), with a tremendous impact worldwide. Besides its function as a pathological calcification inhibitor, vitamin K-dependent protein Gla-rich protein (GRP) was shown to act as an anti-inflammatory agent independently of its gamma-carboxylation status. Although GRP’s therapeutic potential has been highlighted, its low solubility at physiological pH still constitutes a major challenge for its biomedical application. In this work, we produced fluorescein-labeled chitosan-tripolyphosphate nanoparticles containing non-carboxylated GRP (ucGRP) (FCNG) via ionotropic gelation, increasing its bioavailability, stability, and anti-inflammatory potential. The results indicate the nanosized nature of FCNG with PDI and a zeta potential suitable for biomedical applications. FCNG’s anti-inflammatory activity was studied in macrophage-differentiated THP1 cells, and in primary vascular smooth muscle cells and chondrocytes, inflamed with LPS, TNFα and IL-1β, respectively. In all these in vitro human cell systems, FCNG treatments resulted in increased intra and extracellular GRP levels, and decreased pro-inflammatory responses of target cells, by decreasing pro-inflammatory cytokines and inflammation mediators. These results suggest the retained anti-inflammatory bioactivity of ucGRP in FCNG, strengthening the potential use of ucGRP as an anti-inflammatory agent with a wide spectrum of application, and opening up perspectives for its therapeutic application in CIDs.     

Adaptive link layer strategies for energy efficient wireless networking

Low power consumption is a key design metric for portable wireless network devices where battery energy is a limited resource. The resultant energy efficient design problem can be addressed at various levels of system design, and indeed much research has been done for hardware power optimization and power management within a wireless device. However, with the increasing trend towards thin client type wireless devices that rely more and more on network based services, a high fraction of power consumption is being accounted for by the transport of packet data over wireless links [28]. This offers an opportunity to optimize for low power in higher layer network protocols responsible for data communication among multiple wireless devices. Consider the data link protocols that transport bits across the wireless link. While traditionally designed around the conventional metrics of throughput and latency, a proper design offers many opportunities for optimizing the metric most relevant to battery operated devices: the amount of battery energy consumed per useful user level bit transmitted across the wireless link. This includes energy spent in the physical radio transmission process, as well as in computation such as signal processing and error coding. This paper describes how energy efficiency in the wireless data link can be enhanced via adaptive frame length control in concert with adaptive error control based on hybrid FEC (forward error correction) and ARQ (automatic repeat request). Key to this approach is a high degree of adaptivity. The length and error coding of the atomic data unit (frame) going over the air, and the retransmission protocol are (a) selected for each application stream (ATM virtual circuit or IP/RSVP flow) based on quality of service (QoS) requirements, and (b) continually adapted as a function of varying radio channel conditions due to fading and other impairments. We present analysis and simulation results on the battery energy efficiency achieved for user traffic of different QoS requirements, and describe hardware and software implementations.