Interference Coordination: Random Clustering and Adaptive Limited Feedback

Interference coordination improves data rates and reduces outages in cellular networks. Accurately evaluating the gains of coordination, however, is contingent upon using a network topology that models realistic cellular deployments. In this paper, we model the base stations locations as a Poisson point process to provide a better analytical assessment of the performance of coordination. Since interference coordination is only feasible within clusters of limited size, we consider a random clustering process where cluster stations are located according to a random point process and groups of base stations associated with the same cluster coordinate. We assume channel knowledge is exchanged among coordinating base stations, and we analyze the performance of interference coordination when channel knowledge at the transmitters is either perfect or acquired through limited feedback. We apply intercell interference nulling (ICIN) to coordinate interference inside the clusters. The feasibility of ICIN depends on the number of antennas at the base stations. Using tools from stochastic geometry, we derive the probability of coverage and the average rate for a typical mobile user. We show that the average cluster size can be optimized as a function of the number of antennas to maximize the gains of ICIN. To minimize the mean loss in rate due to limited feedback, we propose an adaptive feedback allocation strategy at the mobile users. We show that adapting the bit allocation as a function of the signals' strength increases the achievable rate with limited feedback, compared to equal bit partitioning. Finally, we illustrate how this analysis can help solve network design problems such as identifying regions where coordination provides gains based on average cluster size, number of antennas, and number of feedback bits.Comment: submitted to IEEE Transactions on Signal Processin

Blood soluble interleukin 1 receptor accessory protein levels are consistently low throughout the menstrual cycle of women with endometriosis

BACKGROUND: A deficiency in the counter-regulatory mechanisms of interleukin 1 (IL1) may play a significant role in endometriosis pathogenesis and associated chronic inflammation. The aim of this study was to investigate peripheral blood levels of soluble IL1 receptor accessory protein (sIL1RAP), a potent natural inhibitor of IL1, in women with and without endometriosis. METHODS: Peripheral blood samples were collected from women with endometriosis (n = 47) consulting for infertility, pelvic pain or tubal ligation, in whom the disease was diagnosed at laparoscopy. Control healthy women (n = 27) were requesting tubal ligation or reanastomosis and had no visible evidence of endometriosis at laparoscopy. sIL1RAP levels were determined by ELISA, whereas estradiol (E2) and progesterone (P4) levels were determined by competitive immunoassays. RESULTS: sIL1RAP levels were significantly decreased in women with early endometriosis stages compared to controls (p < 0.05) and markedly during the proliferative phase of the menstrual cycle (p < 0.001). Actually, while sIL1RAP were significantly increased in the proliferative compared to the secretory phase in normal women (p < 0.0001) and peaked at the end of this phase, sIL1RAP remained consistently low and showed non-significant variations throughout the menstrual cycle in women with endometriosis. CONCLUSIONS: Lower circulating levels of sIL1RAP points to a significant impairment in the counter-regulatory mechanisms of IL1, which in view of the cytokine’s potent inflammatory and growth-promoting properties may play a significant role in the pathophysiology of endometriosis

On Imperfect CSI for the Downlink of a Two-Tier Network

International audienceIn this paper, we consider a hierarchical two-tier cellular network where a macrocell is overlaid with a tier of randomly distributed femtocells. We evaluate the combined effect of uncoordinated cross-tier interference, feedback delay, and quantization errors on the achievable rate of transmit beamforming with imperfect channel state information (CSI). We model the femtocell spatial distribution as a Poisson point process (PPP) and the temporal correlation of the channel according to a Gauss-Markov model. Using stochastic geometry tools, we derive the probability of outage at the macrocell users as a function of the temporal correlation, the femtocell density, and the feedback rate. We compute the maximum average achievable rate on the downlink of the macrocell network using a properly designed rate backoff scheme. We show that transmit beamforming with imperfect CSI is a viable option for the downlink of a two-tier cellular network, and that rate backoff recovers the loss in rate due to packet outage

Spatial Interference Mitigation for Multiple Input Multiple Output Ad Hoc Networks: MISO Gains

International audienceWe consider spatial interference mitigation at the transmitter for multiple input single output ad hoc networks. We apply zero forcing beamforming at the transmitter, and analyze the corresponding network throughput and transmission capacity. Assuming a network with Poisson distributed transmitting nodes and spatially independent Rayleigh fading channels, we apply mathematical tools from stochastic geometry to derive a lower bound on the probability of outage. We derive scaling laws for the transmission capacity and show that for a large number of antennas, the maximum density of concurrently transmitting nodes scales linearly with the number of antennas at the transmitter, for a given outage constraint. Numerical results show that the network throughput achieved by interference nulling at the transmitter is comparable to that achieved by interference cancellation at the receiver

A New Algorithmic Approach for Detection and Identification of Vehicle Plate Numbers

This work proposes a method for the detection and identification of parked vehicles stationed. This technique composed many algorithms for the detection, localization, segmentation, extraction and recognition of number plates in images. It is acts of a technology of image processing used to identify the vehicles by their number plates. Knowing that we work on images whose level of gray is sampled with (120×180), resulting from a base of abundant data by PSA. We present two algorithms allowing the detection of the horizontal position of the vehicle: the classical method “horizontal gradients” and our approach “symmetrical method”. In fact, a car seen from the front presents a symmetry plan and by detecting its axis, that one finds its position in the image. A phase of localization is treated using the parameter MGD (Maximum Gradient Difference) which allows locating all the segments of text per horizontal scan. A specific technique of filtering, combining the method of symmetry and the localization by the MGD allows eliminating the blocks which don’t pass by the axis of symmetry and thus find the good block containing the number plate. Once we locate the plate, we use four algorithms that must be realized in order to allow our system to identify a license plate. The first algorithm is adjusting the intensity and the contrast of the image. The second algorithm is segmenting the characters on the plate using profile method. Then extracting and resizing the characters and finally recognizing them by means of optical character recogni-tion OCR. The efficiency of these algorithms is shown using a database of 350 images for the tests. We find a rate of lo-calization of 99.6% on a basis of 350 images with a rate of false alarms (wrong block text) of 0.88% by image

Fusion of basic algorithms for detection and localization of vehicle plate numbers

Institut des Systèmes Intelligents et de Robotiqu

Automatic system recognition of Lebanese license plates

License Plate Recognition is an image-processing technology that is used to identify vehicles by their Lebanese license plates. A license plate reader works by extracting the characters from an image. This technology is used for many applications such as toll booths, parking decks, border control, and law enforcement. As a solution to the problem of monitoring the tremendous number of vehicles for law enforcement and security, we use two methods of classifying the Lebanese plate in several areas: Labeling and K-Mean. Then, we have to extract from the plate the two classifications, which are the French line and the Arabic line. We separate each character from each line using the vertical profile method. Then we would recognize the characters by the algorithm of the K-PPV with a rate of recognition of the characters: The Arabic writing is of 82% and the Western writing is of 91 %. Finally we use a vote method between the two writings to increase the rate of recognition up to 93%

Data Sharing Coordination and Blind Interference Alignment for Cellular Networks

International audienceWe consider coordination in a multi-user multiple input single output cellular system. In contrast with existing base station cooperation methods that rely on sharing CSI with or without user data to manage interference, we propose to share user data only. We consider a system where blind interference alignment (BIA) is applied to serve multiple users in each cell. We apply interference coordination through data sharing to mitigate other-cell interference at the cell-edge users. While BIA mitigates intra-cell interference in MU-MISO systems, it does not address the problem of inter-cell interference. We apply interference coordination through data sharing to mitigate inter-cell interference at the cell-edge users. We propose a new cooperative BIA scheme that takes into account the users whose data is being shared between adjacent base stations. We derive the achievable sum rate with interference mitigation and we compare it to achievable rates with the original BIA strategy. Numerical results show that the achievable sum rate of the cell-edge users with data sharing decreases with increasing number of served users in each cell and increasing number of antennas at the base stations

Tumour necrosis factor-α up-regulates macrophage migration inhibitory factor expression in endometrial stromal cells via the nuclear transcription factor NF-κB

BACKGROUND: A series of controlled changes including proliferation, secretion and menstrual shedding occur in the human endometrium during every normal menstrual cycle. Macrophage migration inhibitory factor (MIF), a multifunctional cytokine with numerous proinflammatory, immunomodulatory and angiogenic properties, appears to be expressed in the human endometrium and to follow a regulated cycle phase-dependent expression, but the mechanisms underlying endometrial MIF expression remain to be fully elucidated. METHODS AND RESULTS: Results from enzyme-linked immunosorbent assay (ELISA) demonstrated a significant dose- and time-dependent increase in MIF secretion by human endometrial cells in response to tumour necrosis factor-alpha (TNF-α) (0.1-100 ng/ml). This increase was also observed at the mRNA level as shown by reverse transcription (RT)-PCR. Curcumin (10−8 mol/l), a known nuclear factor (NF)-κB inhibitor, inhibited the TNF-α-induced pIκB phosphorylation as shown by western blotting, NF-κB translocation into the nucleus as shown by electrophoretic mobility shift assay, and MIF synthesis and secretion as measured by ELISA and RT-PCR. The expression of a dominant-negative NF-κB inhibitor (IκB) significantly decreased the TNF-α-induced MIF promoter activity as analysed by transient cell transfection. CONCLUSIONS: These results indicate clearly that TNF-α up-regulates the expression of MIF in endometrial stromal cells. This took place possibly through NF-κB activation, and may play an important role in the physiology of the human endometriu