Cellular communication is an umbrella term used in biology and more in depth in biophysics, biochemistry and biosemiotics to identify different types of communication methods between living cellulites. Some of the methods include cell signaling among others. This process allows millions of cells to communicate and work together to perform important bodily processes that are necessary for survival. Both multicellular and unicellular organisms heavily rely on cell-cell communication.[1]
Terminal or mobile stations communicates across the Um interface, known as the air interface, with a base BTS in the small cell in which the mobile unit is located. This communication with a BTS takes place through the radio channels. The network coverage area is divided into small regions called cells.
- 2Three stages of cell communication
- 3Local and long distance signaling
- 4Cell signaling and impacts
Intercellular communication[edit]
Intercellular communication refers to the communication between cells.Membrane vesicle trafficking has an important role in intercellular communications in humans and animals, e.g., in synaptic transmission, hormone secretion via vesicular exocytosis. Inter-species and interkingdom signaling is the latest field of research for microbe-microbe and microbe-animal/plant interactions for variety of purposes at the host-pathogen interface.
Three stages of cell communication[edit]
Reception[edit]
A G Protein-coupled receptor within the plasma membrane.
Reception occurs when the target cell (any cell with a receptor protein specific to the signal molecule) detects a signal, usually in the form of a small, water-soluble molecule, via binding to a receptor protein. Reception is the target cell's detection of a signal via binding of a signaling molecule, or ligand. Receptor proteins span the cell’s plasma membrane and provide specific sites for water-soluble signaling molecules to bind to. These trans-membrane receptors are able to transmit information from outside the cell to the inside because they change conformation when a specific ligand binds to it. By looking at three major types of receptors, (G protein coupled receptors, receptor tyrosine kinases, and ion channel receptors) scientists are able to see how trans-membrane receptors contribute to the complexity of cells and the work that these cells do. Cell surface receptors play an essential role in the biological systems of single- and multi-cellular organisms and malfunction or damage to these proteins is associated with cancer, heart disease, and asthma.[2]
Transduction[edit]
When binding to the signaling molecule, the receptor protein changes in some way and starts the process of transduction. A specific cellular response is the result of the newly converted signal. Usually, transduction requires a series of changes in a sequence of different molecules (called a signal transduction pathway) but sometimes can occur in a single step. The molecules that compose these pathways are known as relay molecules. The multistep process of the transduction stage is often composed of the activation of proteins by addition or removal of phosphate groups or even the release of other small molecules or ions that can act as messengers. The amplifying of a signal is one of the benefits to this multiple step sequence. Other benefits include more opportunities for regulation than simpler systems do and the fine- tuning of the response, in both unicellular and multicellular organism.[3]
Response[edit]
A specific cellular response is the result of the transduced signal in the final stage of cell signaling. This response can essentially be any cellular activity that is present in a body. It can spur the rearrangement of the cytoskeleton, or even as catalysis by an enzyme. These three steps of cell signaling all ensure that the right cells are behaving as told, at the right time, and in synchronization with other cells and their own functions within the organism. At the end, the end of a signal pathway leads to the regulation of a cellular activity. This response can take place in the nucleus or in the cytoplasm of the cell. A majority of signaling pathways control protein synthesis by turning certain genes on and off in the nucleus.[4]
Local and long distance signaling[edit]
Local[edit]
Communicating through direct contact is one form of local signaling for eukaryotic cells. Plant and animal cells possess junctions that connect the cytoplasm of cells adjacent to one another. These connections allow for signaling substances that were dissolved in the cytosol to easily pass between the cells that are connected. Animal cells contain gap junctions and can communicate through these junctions in a process called cell–cell recognition. Plant cells are connected through plasmodesmata. Embryonic development and the immune response rely heavily on this type of local signaling. In other types of local signaling, the signaling cell secretes messenger molecules that only travel short distances. These local regulators influence cells in the vicinity and can stimulate nearby target cells to perform an action. A number of cells can receive messages and respond to another molecule within their vicinity at the same time. This process of local signaling within animal cells is known as paracrine signaling.
Long distance[edit]
Hormones are used by both plant and animal cells for long-distance signaling. In animal cells, specialized cells release these hormones and send them through the circulatory system to other parts of the body. They then reach target cells, which can recognize and respond to the hormones and produce a result. This is also known as endocrine signaling. Plant growth regulators, or plant hormones, move through cells or by diffusing through the air as a gas to reach their targets.[3]
Cell signaling and impacts[edit]
There are three different types of basic cell communication: surface membrane to surface membrane; exterior, which is between receptors on the cell; and direct communication, which means signals pass inside the cell itself. The junctions of these cells are important because they are the means by which cells communicate with one another. Epithelial cells especially rely on these junctions because when one is injured, these junctions provide the means and communication to seal these injuries. These junctions are especially present in the organs of most species.[5] However, it is also through cell signaling that tumors and cancer can also develop. Stem cells and tumor-causing cells, however, do not have gap junctions so they cannot be affected in the way that one would control a typical epithelial cell.[6] Upstream cells signaling pathways control the proteins and genes that are expressed, which can both create a means for cancer to develop without stopping or a means for treatment for these diseases by targeting these specific upstream signaling pathways.[7] Much of cell communication happens when ligands bind to the receptors of the cell membrane and control the actions of the cell through this binding.[8] Genes can be suppressed, they can be over expressed, or they can be partially inhibited through cell signaling transduction pathways. Some research has found that when gap junction genes were transfected into tumor cells that did not have the gap junction genes, the tumor cells became stable and points to the ability of gap junction genes to inhibit tumors.[6] This stability leads researchers to believe that gap junctions will be a part of cancer treatment in the future.
Communication in cancer[edit]
Cancer cells will often communicate via gap junctions, which are proteins known as connexins. These connexins have been shown to suppress cancer cells, but this suppression is not the only thing that connexins facilitates. Connexins can also promote tumor progression; therefore, this makes connexins only conditional tumor suppressors.[5] However, this relationship that connects cells makes the spreading of drugs through a system much more effective as small molecules can pass through gap junctions and spread the drug much more quickly and efficiently.[9] The idea that increasing cell communication, or more specifically, connexins, to suppress tumors has been a long, ongoing debate[10] that is supported by the fact that so many types of cancer, including liver cancer, lack the cell communication that characterizes normal cells.
See also[edit]
References[edit]
- Analysis of connexin expression during mouse Schwann cell development identifies Connexin29 as a novel marker for the transition of neural crest to precursor cells. Authors/Editors/Inventors: Li, Jing (Author); Habbes, Hans-Werner (Author); Eiberger, Juergen (Author); Willecke, Klaus (Author); Dermietzel, Rolf (Author); Meier, Carola (Author) [a]. Glia. Vol. 55 (1). JAN 1 2007. 93-103
- A rate equation approach to elucidate the kinetics and robustness of the TGF-beta pathway. Authors/Editors/Inventors:Melke, Pontus (Author); Jonsson, Henrik (Author); Pardali, Evangelia (Author); ten Dijke, Peter (Author); Peterson, Carsten (Author) [a]. Biophysical Journal. Vol. 91 (12). DEC 2006.
- Man1, an inner nuclear membraneprotein, regulates vascular remodeling by modulating transforming growth factor beta signaling. Ishimura, Akihiko (Author); Ng, Jennifer K. (Author); Taira, Masanori (Author); Young, Stephen G. (Author); Osada, Shin-ichi. Development (Cambridge). Vol. 133 (19). OCT 1 2006.
- Protein expression changes in the nucleus accumbens and amygdala of inbred alcohol-preferring rats given either continuous or scheduled access to ethanol. Bell, R. L. (Author) [a]; Kimpel, M. W. (Author); Rodd, Z. A. (Author); Strother, W. N. (Author); Bai, F. (Author); Peper, C. L. (Author); Mayfield, R. D. (Author); Lumeng, L. (Author); Crabb, D. W. (Author); McBride, W. J. (Author); Witzmann, F. A. (Author): Alcohol. Vol. 40 (1). AUG 2006. 3-17
- ^Reece, Jane B. (September 27, 2010). Campbell Biology (9 ed.). Benjamin Cummings. p. 205. ISBN978-0-321-55823-7.
- ^'www.sciencedaily.com/releases/2007/07/070703171935.htm'. www.sciencedaily.com. Retrieved 2016-04-17.
- ^ abReece, Jane B (Sep 27, 2010). Campbell Biology. Benjamin Cummings. p. 214. ISBN978-0321558237.
- ^Reece, Jane B. (Sep 27, 2010). Campbell Biology (9th ed.). Benjamin Cummings. p. 215. ISBN978-0-321-55823-7.
- ^Loewenstein, Werner R. (1972-02-01). 'Cellular communication through membrane junctions: Special consideration of wound healing and cancer'. Archives of Internal Medicine. 129 (2): 299–305. doi:10.1001/archinte.1972.00320020143012. ISSN0003-9926. PMID4333645.
- ^ abSignal Transduction and Communication in Cancer Cells. The New York Academy of Sciences. 2004. ISBN978-1-57331-559-3.
- ^Lu, Kun Ping (2004-04-01). 'Pinning down cell signaling, cancer and Alzheimer's disease'. Trends in Biochemical Sciences. 29 (4): 200–209. doi:10.1016/j.tibs.2004.02.002. PMID15082314.
- ^Schlessinger, Joseph (2000-10-13). 'Cell Signaling by Receptor Tyrosine Kinases'. Cell. 103 (2): 211–225. doi:10.1016/S0092-8674(00)00114-8. PMC2914105.
- ^Naus, Christian C.; Laird, Dale W. (2010-06-01). 'Implications and challenges of connexin connections to cancer'. Nature Reviews Cancer. 10 (6): 435–441. doi:10.1038/nrc2841. ISSN1474-175X. PMID20495577.
- ^Loewenstein, W. R.; Kanno, Y. (1966-03-19). 'Intercellular Communication and the Control of Tissue Growth: Lack of Communication between Cancer Cells'. Nature. 209 (5029): 1248–1249. Bibcode:1966Natur.209.1248L. doi:10.1038/2091248a0.
Further reading[edit]
Books
- Handbook of Cell Signaling / edited by Ralph Bradshaw and Edward Dennis. Academic Press, 2009. ISBN0-12-374145-9
- Cox, Rody P., 1926-). [1974]. Cell communication, edited by Rody P. Cox. New York, Wiley. ISBN0-471-18135-8
- Cell communication in health and disease : readings from Scientific American magazine / edited by Howard Rasmussen. New York : Freeman, c1991. xii, 185 p. : ill. (some col.) ; 24 cm. ISBN0-7167-2224-0
- Cell communication in nervous and immune system / [edited by] Eckart D. Gundelfinger, Constanze I. Seidenbecher, Burkhart Schraven. 1st ed. New York : Springer, 2006. ISBN3-540-36828-0.
Journals
- Cell adhesion & communication. Yverdon, Switzerland ; New York : Harwood Academic Publishers, 1993-c2000. Vol. 1, issue 1 (May 1993)-v. 7, no. 6 (2000). ISSN1061-5385
- Cell communication & adhesion. Basingstoke, Hants, UK : Harwood Academic Publishers, c2001-). Vol. 8, issue 1 (2001)- ISSN1541-9061
- Friedman, Michael, 1955-). Cell communication : understanding how information is stored and used in cells / Michael Friedman and Brett Friedman. 1st ed. New York : Rosen Pub. Group, 2005. ISBN1-4042-0319-2
- Intercellular communication / edited by Feliksas Bukauskas. Manchester ; New York : Manchester University Press ; New York, N.Y., USA : Distributed exclusively in the USA and Canada by St. Martin’s Press, c1991. ISBN0-7190-3269-5
- Intercellular communication / edited by Walmor C. De Mello. New York : Plenum Press, c1977. Description: ISBN0-306-30958-0
- International Leucocyte Culture Conference (15th : 1982 : Asilomar and Pacific Grove, Calif.) Intercellular communication in leucocyte function : proceedings of the 15th International Leucocyte Culture Conference, Asilomar, Pacific Grove, California, December 1982 / [edited by] John W. Parker and Richard L. O’Brien. Chichester ; New York : Wiley, c1984. ISBN0-471-90161-X :
- Fleming, Andrew J.(Ed.). (2005). Intercellular communication in plants. Oxford : Blackwell. ISBN1-4051-2068-1
- Intercellular communication in plants : studies on plasmodesmata / edited by B. E. S. Gunning and A. W. Robards.Berlin ; New York : Springer-Verlag, 1976. ISBN0-387-07570-4
- Intercellular communication through gap junctions / editors, Y. Kanno ... [et al.]. Amsterdam ; New York : Elsevier, 1995. ISBN0-444-81929-0
Retrieved from 'https://en.wikipedia.org/w/index.php?title=Cellular_communication_(biology)&oldid=919358937'
When a mobile user travels from one area of coverage or cell to another cell within a call’s duration the call should be transferred to the new cell’s base station. Otherwise, the call will be dropped because the link with the current base station becomes too weak as the mobile recedes. Indeed, this ability for transference is a design matter in mobile cellular system design and is call handoff.
![Ppt Ppt](/uploads/1/2/5/8/125853271/533774348.jpg)
Two basic types of handoff are defined -- viz.hard handoff and soft handoff.
With hard handoff, the link to the prior base station is terminated before or as the user is transferred to the new cell’s base station. That is to say that the mobile is linked to no more than one base station at a given time. Initiation of the handoff may begin when the signal strength at the mobile received from base station 2 is greater than that of base station 1. The signal strength measures are really signal levels averaged over a chosen amount of time. This averaging is necessary because of the Rayleigh fading nature of the environment in which the cellular network resides. A major problem with this approach to handoff decision is that the received signals of both base stations often fluctuate. When the mobile is between the base stations, the effect is to cause the mobile to wildly switch links with either base station. The base stations bounce the link with the mobile back and forth. Hence the phenomenon is called ping- ponging. Besides ping ponging this simple approach allows too many handoffs. [1] It has been shown in early studies that much of the time the previous link was well adequate and that handoffs occurred unnecessarily. A better method is to use the averaged signal levels relative to a threshold and hysteresis margin for handoff decision. Furthermore, the condition should be imposed that the target base station’s signal level should be greater than that of the current base station.
The handoff should take place at point A for the choice of Threshold 1 or Threshold 2. The handoff should take place at point B for Threshold 3. In has now been shown in practice that using the hysteresis margin greatly reduces the number of unneeded handoffs. However, there is a delay factor involved here. It will be shown later that one may set up optimum trade off values for the parameters threshold and hysteresis to obtain a tolerable delay.
Because of the increasing demand for wireless services, the available channels within the cells become insufficient to support the growing number of users. To increase the system capacity, techniques such as cell splitting and sectoring may be implemented. Using microcells also improves cellular system capacity, and it is an attractive alternative to the two former mentioned techniques. [2] While the group of cells may maintain a particular area of coverage, the co-channel interference is reduced. Decreasing the co-channel interference increases the system capacity without trunking inefficiency degradation inherent to sectoring. However, innate to microcells is the increase in frequency of handoffs. So we seek efficient decision algorithms to achieve less unnecessary handoffs, yet more reliable handoffs with low blocking probability and low probability of lost calls. Mobiles moving around in microcells will face line of sight (LOS) handoffs and non line of sight (NLOS) handoffs. In the case of NLOS, completely reliable handoffs are difficult to achieve. A problem with microcells is the so called corner effect. When a mobile station moves around a corner such as at a street intersection, there can be a sudden drop in the received signal level. It loses its LOS component with the serving base station. Now if the mobile user does not link up with this new base station B fast enough, the call gets dropped. Furthermore, the mobile can cause interference to the new base station. The base station is unable to regulate the power of the mobile and users within this cell are blocked.
In the cellular design, one could carefully plan so that this can’t happen. That is lay out the cells in such a way that no corner effect will ever be encountered. This cannot always be practically done. Measures are taken in handoff design to help alleviate this problem. We may use a fast forward handoff as the old base station is dropped. Decentralizing the handoff decision, as in the case of the mobile assisted handoff, often achieves this fast forward handoff decision. [1] With decentralizing, it is advantageous that the central switch does not have to make the handoff decisions for every mobile user. This amounts to a saving in system resources.
A problem with faster handoff is that we lose the benefits associated with signal averaging and hysteresis. As was mentioned before, this was helpful in mitigating unnecessary handoffs and ping ponging. However as is now clear, the time of handoff is critical in mircocellular systems and we may not tolerate the delay that comes with hysteresis windows. The handoff must be fast. Now recall that in order to initiate a handoff, the movement of the mobile station from one cell to another must be detected. A reliable method to make this detection and to accommodate the movement is to measure the received signal strengths to the base stations and from the user. In order to avoid excessive and inaccurate handoffs, an averaging of the received signal levels is performed as well as implementing a hysteresis margin. The total handoff delay is the sum of the signal averaging delay and the hysteresis delay. We seek to make this delay small. [3] develops an analytic approach to select the signal averaging time and hysteresis delay in order to obtain an optimum tradeoff between those two parameters as well as a tradeoff between the total delay time and the number of allowable unnecessary handoffs. In [3], some important parameters are given mathematical expressions. It is shown that the probability of an unnecessary handoff is given as:
where f(x) is considered as
D L is the difference between the two received signal levels due to the pathloss difference from the two base stations involved in the handoff. And, h is the hysteresis level.
For macrocells, the total delay time is:
T denotes the signal averaging windowK2 represents a path loss constant
Krv represents the normalized distance from the mobile station to base station.
![Communication Communication](https://www.slideteam.net/media/catalog/product/cache/1/thumbnail/543x403/7bdaa8c8f4730ca595245b6188ae0994/0/9/0914_different_designs_of_cellular_radio_mobile_towers_for_wireless_communication_ppt_slide_Slide03.jpg)
For microcells, the total delay time is:
dcor denotes the drop in signal level experienced at a street corner and is determined experimentally. The analysis shows that there exists compromises between the parameters of averaging time and hysteresis delay. It is evident that for microcells we may wish to choose short averaging time and a larger hysteresis. The converse is clear for macrocells. The main point here is that optimum parameter values may be selected for a tolerable delay in conjunction with some tolerable probability of unnecessary handoff.
By using alternate antenna heights working at different power levels, it is possible to have different size cells coexist within a single geographic framework. Thus may be implemented the so called umbrella cell consisting of two or more levels. That is a macrocell, which contains perhaps a grid of microcells.
Users in this system are assigned to a particular cellular level based on the mobile transmitter’s speed. [4] The umbrella cell system is used to minimize the many handoffs incurred by high speed mobiles while providing capacity that is inherent to microcells for slow moving users. Handoffs from microcell to microcell can be avoided. Now the slow moving users are placed into the service of a microcell and retain service therein until an increase in mobile transmitter speed overtakes some deciding measure and is therefor urged into a macrocell. However, in the real cellular system, the speed is not really known. Fortunately, there are a couple of common ways to estimate the user speed. One way is to use the statistics of the dwell time. The dwell time is defined as the amount of time over which a call is maintained within a particular cell. Obviously, the dwell time is dependent upon the mobile station’s speed. Based on information of the dwell time, a rough estimate of the user speed may be obtained. Further, the estimate may be improved if the mobile’s past behavior is memorized and accounted for. [3100] Given n dwell times, mobile station speed may be estimated as follows. First assume that the mobile speed is uniform over an interval [a,b]. It is found that the maximum likelihood (ML) estimate is:
and the maximum squared error (MMSE) estimate is:
ci depends on the type of handoff -- i.e. micro to micro, micro to macro etc.
In [5] four strategies are proposed to estimate speed so that an assignment can be made for fast moving mobiles to the macro layer and slower users to the micro layer.
The first two strategies are based only on the most recent dwell time t. The third and fourth acquire speed estimations based on the ML estimator and MMSE estimator respectively.
Results from models and real systems have shown that there is a marked reduction in handoffs for strategy 3 and 4 especially in low traffic situations.Strategy 1) All the users that are new are placed in a microcell. The idea is to simply move the user to a larger cell if the dwell time spent in that microcell is short in relation to a threshold parameter T. Strategy 2) Like strategy 1, all new users are put into the service of a microcell. However here, users are updated regularly between cell levels base on continuous dwelling duration measurements. Strategy 3) Make a record of all past cell dwell times spanning a call. Use ML estimators to approximate the speed. Make an appropriate level handoff decision based on those estimates. Strategy 4) This is similar to strategy 3 except that MMSE is used to estimate mobile station speed.
Another method to estimate the mobile speed for optimum cell level placement is to take advantage of diversity reception. As will be seen for soft handoff in CDMA systems, it is good practice to use selection diversity to mitigate the effects of Rayleigh fading . Mobile velocity can be estimated from Doppler frequency. Recall that with selection diversity two or more antennas are used. A receiver will switch to the strongest received signal branch. To estimate the Doppler frequency, the rate of switching is measured. Based upon the autocorrelation of Rayleigh fading, the following relation exists between switching rate NBS and Doppler frequency fD. [7]
This is a good approximation and the Doppler measure here is used to estimate the speed.
CDMA uses soft handoff. Soft handoff is beneficial because it reduces interference into other cells and improves performance by using macro diversity. Also, it has been shown that soft handoff can extend coverage area by as much as a factor of 2.5. [6] Recall hard handoff. There, a handoff was performed when the signal strength of an adjacent cell exceeded that of the current cell by some threshold. In CDMA, the adjacent cell frequencies are just the same as those of the current cell. Therefor, using this hard handoff technique would cause severe interference into neighbor cells and thus degrade capacity. In a CDMA system with soft handoff, each mobile user is connected to two or more base stations at a time. The base station with the highest relative strength seen from the mobile is given the control of the mobile user’s call. Also, because a user in soft handoff is connected to several adjacent base stations, probability of a lost call is reduced. Soft handoff fits nicely into the structure of CDMA. As was just mentioned, in the uplink the user signal may be received by several or more base stations. This is because of CDMA’s reuse factor of one. In the downlink, the signals from the base stations can be coherently combined as they are seen as multipath components. Here will be described the soft handoff procedure. But first, it is necessary to show the following definitions. [6]
- Active set is the set of base stations that are involved with the mobile station during the soft handoff.
- Active set update is when a change in the active set occurs. An update occurs when a candidate base station exceeds the add threshold, when an old base station has been below the drop threshold for too long, or the active list becomes too large.
- Discard set are the base stations that are currently members of the active set but will be dropped because they are no longer qualified as such.
- Candidate set are those neighboring base stations to the current one.
To summarize, soft handoff is advantageous over hard handoff because the mobile does not lose contact with the system during handoff execution. Ping ponging is eliminated and an extra measure of performance is obtained through diversity combining to mitigate fading. Furthermore, more control may be given to the mobile in handoff decisions. This autonomous handoff decision ability , selection diversity, and inherent improvement of reliable handoffs with fewer unnecessary decisions, make soft handoff an attractive choice meriting further study as it is being used in third generation CDMA.
References
[1] Mikael Gudmundson, 'Analysis of Handover Algorithms.', IEEE Vehicular Technology Conference July 1991, pp537-542
[2] Dr W.C.Y. Lee, 'Smaller Cells for Greater Performance', IEEE Communications Magazine , Nov. 1991, pp19-23
[3] Mahmood Zonoozi, Prem Dassanayake, M. faulkner, 'Optimum Hysteresis, Signal Averaging Time and Handover Delay', IEEE Vehicular Technology Conference, March 1997, pp 310-313
[4] K. Ivanov, G. Spring, 'Mobile Speed Sensitive Handover in a Mixed Cell Environment', IEEE Vehicular Technology Conference, 1995, pp 892- 896
[5] Chi Wan Sung, Wing Shing Wong, 'User Speed Estimation and Dynamic Channel Allocation in Hierarchical Cellular Systems', IEEE Vehicular Technology Conference, March 1994, pp91-95
[6] Ojanpera, Prasad, Wideband CDMA for Third Generation Mobile Communications , Artech House Publishers, 685 Canton street Norwood, MA 02062
[7] Kazuo Kawabata, Takaharu Nakamura, Eisuke Fukuda, 'Estimating Velocity Using Diversity Reception', IEEE Vehicular Technology Conference, March 1994, pp371 - 373