Radio Communication - Science topic

Yes, there has been extensive research on participatory program/content production in community radio! It's a crucial aspect of community radio's unique identity and impact. Here are some examples of research areas:

Here are some specific examples of research:

These are just a few examples, and there are many more research projects out there. If you're interested in learning more about specific aspects of participatory content production in community radio, I'd be happy to help you find additional resources.

Remember, research on this topic is ongoing and constantly evolving as community radio adapts to new technologies and social contexts.

Hybrid diversity schemes improve MIMO radio communication by combining diverse techniques like time, frequency, or polarization diversity. They enhance performance by reducing fading effects, thus the reliability gets improved. Factors affecting their effectiveness include channel conditions, antenna configuration, and other system parameters. Moreover, careful optimization is necessary to select the right scheme for a specific MIMO system.

Research in electronic approaches that address rural connectivity deficits in cost-efficient ways would be of interest to countries that host rural populations in remote locations. (E-health is one such approach.)

I suppose this depends on what kind of obstacles you are considering and how they are affecting the signals. If you consider an object that is scattering the signal, then the pathloss will be proportional to (d_1*d_2)^2 where d_1 is the distance from the transmitter to the obstacle and d_2 is the distance from the obstacle to receiver. For a given total propagation distance d_1+d_2, it follows that the pathloss is at its smallest when the scattering object is close to the transmitter or the receiver.

Dear Gul Lakhta ,

There is something basic which you you would like to consider. From the point view of the signals, the interference signal acts in a similar way to noise. When it is added to the symbol signal it will cause that it may be falsely detected if its value is increases such that the combined signal will be located in the neighboring decision regions of the adjacent symbols in the constellation diagram. So the interference and noise have the same effect in the symbol error.

Therefore one speaks not only from S/N ratio but also from the S/(N+I).

The noise has Gaussian amplitude distribution while the interference may not have such distribution because of the nature of the interference.

The interference signal sources are normally known and then they can be subtracted from the composite signal. If after interference cancellation there will be residual interference it will be treated as a noise concerning its effect on the symbol error. In the sense that it will set the S/I +N minimum level to achieve specific bit error rate. You see if N=0 then S/I will set this minimum.

Hope I could answer satisfactorily you question.

Best wishes

.....We have a Pre-Print attached :

Q=sqrt(2) erfc^-1 (2 BER)

I did confuse confuse bandwidth with delay a bit, but not in recent comments, I think, because I realised I was doing it.

Unless the entangled pairs are prepared on earth and then half are sent to Jupiter on the satellite, which would require coherence lifetimes of years (many orders of magnitude above present lifetimes), a signal has to be sent from Jupiter at lightspeed (for instance a photon entangled with the state on Jupiter) to convey the entanglement information between the two sites before the quantum measurement, so that the half of the entangled state can be set up on earth. This means that the actual data rate is still limited by the bandwidth of the lightspeed signals, even if data can be sent with no delay,

I guess if zero delay was possible, it would still be useful, for things like steering a remote vehicle, or conversation.

I expect that each entangled state will carry 1 bit, one Q-bit.

I am not sure instantaneous communication will ever happen. It may. I don't understand it enough to be sure it can't work. I hope it may be possible. It would also raise lots of interesting problems with relativity. I wouldn't invest my pension on it, but I might invest fun money.

In Latin America many community radio production is very active to respond COVID. http://www.corape.org.ec/satelital/produccion/categoria/leyendas_en_shuar

https://radialistas.net/category/series/otras-series/el-dia-despues/

They are in spanish.

V = 0m/s

Therefore, Doppler shift = 0

Dear Tariq Islam ,

Assuming that the transmission coefficients of the channels from the A and B to node C are ha and hb and assume that the transmit signal of A is Sa and that of B is Sb then the received signal at node C rC= ha Sa + hb SB

The power received is rC^2.

This power can be considered an interference which is added to the white noise to determine the threshold of the useful received signal.

So the total noise at the node C= rC^2 +N

The required signal to noise ratio is then given by

C= B log2 (1 + S/( rC^2 +N))

where S is the useful recieved signal power at node C received from the intended node. Bis the bandwidth and C is the maximum bit rate.

Best wishes

It is better to use any text book related to the satellite communication.Go in detail and the after all ,it would be easy to consider some additional parameter( attenuation due to weather/ foliage etc) apart from basics as your have considered previously such power, frequency,polarisation,height,gain etc.

hi...i am able to write a code for single cell massive mimo system for MRC.ZF and MMSE receivers. Did u get the matlab code for multicell massive mimo, please send me..kiranec121@gmail.com

Hi.,

The UE finds the PDCCH specific to it by monitoring a set of PDCCH candidates (a set of consecutive CCEs on which a PDCCH could be mapped) in every subframe. The UE uses its Radio Network Temporary Identifier (RNTI) to try and decode candidates. The RNTI is used to demask a PDCCH candidate's CRC.

For more info:

it's little complicate

1. According to 3GPP, LTE Cat NB1 (NB-IoT) specifies 1 antenna. From the hardware perspective, it should be the same design as regular LTE bands.

2. It seems to be able to support multi-carrier operation

Dear David, imho maybe accuracy in terms of "MHz" is not sufficient, since there's a significant daily and seasonal foF2 variation (i.e. any MHz specification will be much less sufficient let's say for night- than daytime). I will try to check any valid accuracy standard and turn back to you.

Naveed.

You can estimate sensitivity as equal to = 10×log₁₀(kTB)+NF+C⁄N

C/N is the desired carrier to noise ratio. NF is the noise figure of the amplifier.

plug into your numbers and choose a suitable amp.

we have developed a LNA using discrete components with  a NF of 1.0 dB.

Texas Instruments has a device that is interesting.

The DRV134 and DRV135 are differential output

amplifiers that convert a single-ended input to a

balanced output pair. 

I have built discrete 3 OpAmp systems like this, 

but without attention to exact impedance matching. 

HTH, Glen

As the Shannon theory shows, capacity and SINR are trade-able.  In fact there is no nonzero SINR low enough to completely prevent communication!  

This property manifests itself in standards such as Wi-Fi (IEEE802.11) with protocols that respond to degraded channel conditions by adaptively lowering the data rate.  In addition, if the system tries to communicate the same information repeatedly (ARQ) it becomes more reliable at low SNIRs.  The trade-off is increased latency..

So, I'm afraid, as in so much engineering, the answer to your question is "it depends".  To answer your question you first need to know or decide:

It's a complicated field with no "one correct" answer!

The answer to the question is, supposedly by 2020.

There are multiple different trials ongoing or planned for 5G, in different parts of the world. I doubt anyone has pinned down exactly what techniques will become the standard(s), although some candidates often mentioned are massive MIMO and FBMC, as well as channels up in the multiple GHz and multiple 10s of GHz.

On the other hand, you also seem to have answered your own question?

One good way of verifying the proper functioning of your detector is through Monte Carlo simulations. They allow estimating the exact threshold value for guaranteeing a given false alarm probability. I have used this method for the Weibull distribution in the following paper.

Good Luck!

Are you using software or measurements?

Max,

Beamed power is an old old idea.

Do you not remember the SPSS of the 70s? (I guess not...)

The plan to harvest solar power in high orbit, convert it to microwaves, and then beam those microwaves back to the Earth, was interesting.

And the idea was revived by Bob Forward's Starwisp proposal in the 80s.

There's nothing wrong with it except for:

a) The need for large emitters to reduce diffraction spread

b) The need for low-mass and efficient absorbers/converters (optical? microwave?)

It's an old trope to install laser arrays on Mercury and power solar sails to the nearby stars.

Perfectly doable - but to justify it you need deep solar missions - and I suggest that you look at the problem of providing even 1kW of power at Jupiter orbit from the Earth.

(calculate the beam spread for a plausible transmitter, and see how large your 'telescope/laser' needs to be)

The received signal strength depends on the transmitter power, the sensitivity of the receiver  the distance between the transmitter and the receiver and the channel condition. That is if if it is line of sight, Rice or Rayleigh.

So, the most straight forward method is to calibrate the signal strength for a given set of prevailing conditions and devices. That is you determine this relation empirically.

You can also build a system model using matlab to work out such relationship.

You may also solve the problem analytically under simplified propagation conditions.

Phased array are indeed complicated to deploy. A key benefit of Massive MIMO is that a phased array is not needed! The antennas in the array does not have to be jointlu phase calibrated. The user sends an uplink pilot signal and then the base station array measures the combined effect of the channel and the phase rotation in the hardware. When transmitting in the downlink, the base station then "inverts" the phase (= complex conjugation) and thereby cancels out the phase rotation that occurred in the hardware.

The remaining challenge is to make the uplink and downlink reciprocal at a given antenna, since the hardware chains are different although the physical channel is the same. Fortunately, the conversion factor from the uplink to the downlink channel varies slowly and can estimated in practice. This has been done successfully in all the Massive MIMO testbeds that I know about.

The "need" for phased arrays is actually related to one of the "myths" in the following paper:

Emil Björnson, Erik G. Larsson, Thomas L. Marzetta, “Massive MIMO: Ten Myths and One Critical Question,” IEEE Communications Magazine, vol. 54, no. 2, pp. 114-123, February 2016. (http://arxiv.org/pdf/1503.06854)

 Thanks Shanidul Hoque

You might add the random sine waves in the time sequence.

Dear Prasadrayi Rayi,

I hope these materials to be helpful.

Best Luck.

Massive MIMO: Fundamentals and System Designs ( http://liu.diva-portal.org/smash/get/diva2:772015/FULLTEXT01.pdf )

capacity analysis of asymptotically large mimo channels ( attached file)

Dear Zhang,

I think you may be confusing things here. Wireless propagation channels are modeled by three different phenomena:

These different phenomena are depicted in the figure I attached to my answer. As you can see, Rayleigh fading only causes small scale, fast variations of your received power. 

That is why I think your approach is wrong : when you use practical RSSI measurements, you average the received power both on the whole bandwidth of the receiver and on a certain period of time. This averaging makes the effects of fading disappear, and you cannot reconstruct the Rayleigh distribution of the envelope of the received signal afterwards. 

Most likely, you'll see that your measured pathloss will obey a law in d^(-a) where d is the distance and a a coefficient higher than 2, as some obstacles will certainly limit your received power. But, to conclude, I really do not think that you can recreate a Rayleigh fading distribution from your measurements - as you are not measuring the good metric for that.

Hope this can help you,

Best regards, 

Quentin

Hexagonal cell shape is perfect in cellular architecture because it cover an entire area without overlapping.

Satellite radios are most commonly used by consumers in automobiles as it offers better sound quality and more station programming choices over traditional AM and FM radio.Consumers typically pay for Satellite radio programming on a monthly subscription basis.

While mentioning frequency sweep you need to enable Save fields, which is below the frequency setup.....

One more valid point is:

The sweep option you will find only in fast and discreet, but not in Interpolation.

Standard

The real signal is expressed as exp{i o t} + exp{-i o t} = 2 Re exp{i o t}.

In the product ( exp{i o1 t} + exp{-i o1 t} )( exp{i o2 t} + exp{-i o2 t} ), the cross terms give the frequency difference term, while for a complex signal there is no cross term.  It's simple algebra, and that is all what Wignall is implying.  In the Schrödinger equation, the wave function is trully complex, it isn't a calculational trick.

If the medium is non linear, there is a term in f^2 and others of higher orders. If two wave functions superpose, it becomes (f1 + f2)^2, in which there is the considered 2f1.f2 term.

You didn't provide any information about what type of array you're talking about, but the simplest answer is no, you need phase information AND element location information to be able to determine relative time of arrival and corresponding angle of arrival information.  Now, on the other hand, if you're talking about using a directional antenna and you have the ability to rotate said antenna and measure just magnitude, then you can obtain direction of arrival information from just the magnitude pattern information.   This is of course assuming line of sight (plane wave) illumination.  In all cases, multi-path AoA is more complicated.

Now, the above discussion gives you an interesting case to consider.  Assuming you're asking about the beam forming capabilities of a set of dipole elements (a typical wireless antenna system, for example) , consider the directionality of a typical linear dipole array (Yagi, Log Periodic Dipole Array, etc.).  Such antennas achieve directionality in a given frequency range based on the physical spacing of the elements and the direct summation of the received RF signal on each element along a transmission line that connects them.  The frequency dependence is a combination of the element spacing both at the propagation velocity in free space and along the transmission line.  When those phases sum properly, you obtain a single lobe along the direction of the array.  If instead I were to put a detector on each element and sum the resulting DC voltage, I would just get a higher DC voltage.  There would be no directionality, since each element would respond like a dipole to the same field regardless of direction.  (Actually there would be mutual coupling effects between the elements which DO give some directional behavior even in this case, but I'm ignoring that for now to make a point.  In fact, one directional antenna design consists of two passive resonant elements with a single dipole element in between!)  So you see, without phase information, even a common passive directional antenna wouldn't work.

Golay, Gold and Kazami are the popular ones.

Channel Estimation is based on LS, ML, MAP, MMSE methods but it can be categorized to training-based, semi-blind and blind methods. Nowaday, pilot-aided methods are used for channel estimation of fast-varying channels.

Any embedded board with Ethernet port or WiFi should meet the requirement. We find several boards more 25 numbers. 

But IoT with CDMA is evolving and we find limited boards.

One such board is available from Microchip at :

Another link is http://www.u-blox.com/en/c027-iot-starter-kit.html

Its hard to implement it as ZigBee gives only 250 kbps data rate and it is theoretical. In practical it may be less. It might be possible if you compress your voice signal but it will take more time to transmit. Do you know how to configure ZigBee?

A whole lot of 3G proposals were classified as IMT-2000 at the time.  Such standards included CDMA DS, CDMA MC, and some TDD technologies.  The ITU-R went through an evaluation process of them all.  You can find the guidelines for evaluation, known as M.1225, dated 1997 on the ITU web site (see link).  The individual standards bodies did the work and submitted the results to the ITU.  Its probably 1998-1999 time frame.

The error you get because there is some functions which are not defined in the code such as "f_sr_cos_p", for that you have to write an adequate functions, and it should work.

best regards

Hi,

I'm not working on cognitive uwb radio right now, but I did in the past.

You can check the following:

Granelli, Fabrizio, and Honggang Zhang. "Cognitive ultra wide band radio: a research vision and its open challenges." 2nd International Workshop on Networking with Ultra Wide band and Workshop on Ultra Wide Band for Sensor Networks. 2005.

Granelli, Fabrizo, et al. "Research advances in cognitive ultra wide band radio and their application to sensor networks." Mobile Networks and Applications 11.4 (2006): 487-499.

Best,

Fabrizio

I don't have any experience in commercial base but we (my team) did it as experimental base. We connected RFID kit with Zigbee module in real test bed. We also expand WSN with Zigbee module with 4 to 5 nodes. 

thank you for sharing your intelligence

Massive MIMO uses multiuser beamforming to focus each signal on its intended user. By adding up the contributions from M antennas coherently, an array gain of M is achieved. This allows to decrease the total transmit power at the base station by M without decreasing the coverage. Please note that the total transmit power of the base station can be pretty large even if the power per antenna is low.

Are the sensors autonomous or are they powered by the vehicle? Is this shovel attached to a vehicle. In Dutch we call the whole machine (see picture a shovel). Normally you could benefit from the reflections from the environment. Could this be an option in your case? An other possibility is to place the antennas on the back of the shovel. What also could happen, because the shovel is in the near field of the antenna, that it will be detuned. Did you investigate that? Furthermore the antenna will introduce some current into the metal and thus diffraction on the edges of the shovel, this could be in you advance.

LTE FDD Radio Frame structure :-

In time domain :

1) 10 ms long with 10 subframes each of 1 ms.

2) Each subframe has two slots of 0.5 ms each & each slot has 7 orthogonal symbols.

In freq domain :

1) 72 subcarriers each of 15khz bandwidth & grouped into 6 RBs (PRBs).

Collectively :

1) An entity consisting of a subframe (1ms) of time domain & 12 subcarriers is known as Scheduling Block (SB).

2) An entity consisting of a slot (0.5ms) of time domain & 12 subcarriers is known as Resource Block (RB).

3) An entity consisting of a orthogonal symbol (0.071428 ms) & one subcarrier (15khz) is known as Resource Element (RE).

So a LTE radio frame consists of 10 subframes (i.e. total 1 ms) in time domain & 72 subcarriers (i.e. total 1080 Khz) in freq domain.

Why 15kHz? It is because UMTS and LTE have the same clock timing!

I’ll explain it with an example.

In LTE for BW=5MHz, there is 300 subcarrier. (with 10% guard band, 4.5MHz/15KHz=300)

But we know that in IFFT/FFT transformation, Nfft should be a power of 2 (to speed-up the FFT operation). 300 is not a power of 2 and the next power of two is 512.

Fs = Nfft x Δf (because Fs=1/Ts , Ts=Tsym/Nfft and Δf=1/Tsym=15kHz)

For BW=5MHz, Fs=512*15kHz=7.68MHz => Fs=2*3.84MHz

(3.84MHz is chip rate in UMTS).

We could reach to our timing goals by sub-carrier spacing equal to 7.5KHz or 30KHz also, but 15KHz is an agreement base on multicarrier transmission challenges (ISI , Doppler effect, …).

Why 12 sub-carriers is there in a RB? I think if we notice to total subcarrier in different LTE Bandwidth we can guess the answer. 20MHz->1200subcarrier, 15MHz->900, 10MHZ->600, 5MHz->300, 3MHz->180, 1.4MHZ->84 (with 10% guard band for all), 12 is the greatest common divisor of them.

Why 7 Time slots for a RB?

We know that RB is the smallest block that is allocated to an UE in LTE. I think RB Time slots number’s value is an agreement base on latency (.5mSec for a RB) and traffic efficiency (84symbol/.5msec). (84 is equal to 12 subcarrier*7 Recourse Elements). In wimax (IEEE 802.16d), block size is not fixed.

For more information you can check the link that was provided by me.

Salt water is a medium that has a high relative dielectric permittivity (around 80) and is also able (rather poorly) to behave as electrical conductor. Conductivity (around 4 siemens/m) involves losses when a wave propagates in such a medium. Penetration depth of radiowaves are however strongly dependant of the wavelength/ frequency spectrum of the transmitted wave. Submarine electromagnetic transmissions are possible only at a few Hertz or a few tens of Hertz (depending on numerous factors including the distance of course). The right figure of merit is the skin depth (defined in many standard textbooks)

I agree with Kishore and think that NetSim is one of the best tools for 802.22 simulation.

First you have to eliminate bad matching in input, that means using impedance transformers or BALUN network. But if you have the perfectly matched antenna, still there would not be perfect radiation; because the antenna structure determines how the current would distribute on antenna. And when the current is not distributed to radiate, the radiation efficiency degraded.

One traditional way is to increase dielectric constant but in this way the antenna performance become narrow-band.

The other way is to observe the current distribution on antenna structure and try to reshape its structure so maximum current get closer to its edge. This again might result in bandwidth degradation.

For radio sound broadcasting in the upper HF broadcast bands (6 to 30 MHz) both horizontally and vertically polarized antennas will work, although horizontal polarization is more common. This is logical is, as these frequencies are generally used to reach far away (500-5000 km) areas by means of ionospheric radio wave propagation. This calls for directional antennas to beam the energy towards the coverage area, both in the horizontal and the vertical plane. Using horizontal polarization gives addition antenna gain due to the ground reflection near the antenna.

For radio sound broadcasting in the tropical bands (2 to 3 MHz) or in the lower shortwave bands (3 to 7 MHz) the antennas used may also be horizontally polarized antennas suspended at 0.1 to 0.2 lambda above ground. These antennas radiated straight upwards and that radiation is reflected by the ionosphere to cover a continuous area around the transmitter with a radius of 300-500 km (typically) with excellent signal strength. This propagation mechanism is called Near Vertical Incidence Skywave (NVIS).

In the higher medium wave (1 to 1.5 MHz) ionospheric radio wave propagation is still possible at nighttime and sufficiently high horizontally polarized antennas would work at night to cover longer distances. Vertical polarization may also be used for this. Daytime absorption in the ionosphere, however, is very high.

NVIS would be possible at nighttime, but suspending horizontal antennas much lower than 0.1 lambda above ground requires either an extensive ground screen or the amount of power lost into the ground below the antenna will be very high.

Ionospheric propagation is not possible or not practical at frequencies below 1 MHz. Therefore most broadcast station on long or medium wave (0.1 - 1.5 MHz) are designed for ground wave propagation, for which vertically polarized antennas work best. These antennas also need extensive ground screens, as the ground is part of the antenna itself and ground losses directly cause reduction of the antenna efficiency.

Antenna gain, ground losses and voltages between antenna and earth for horizontal and vertical antennas with `thin´ elements can be modeled quite well with free Method of Moments (MoM) antenna packages such as NEC-2 or NEC-4. Be sure to use Sommerfeld ground, and please compare your results with good antenna books (Kraus, Jasik) to avoid common simulation pitfalls. If your simulation are contradicting common theory, they might be wrong :-)

The critical frequency of the ionosphere is not a fixed value. It roughly varies with time of day, day of the year, and the 11-year long solar cycle. Short term variation is influence by many factors, of which the solar radiation and the earth magnetic field are the main drivers.

Solar flares may disturb the more usual arrangement of the ionosphere, and can be seen as anomalies in ionospheric radio wave propagation, sometimes even totally disrupting all ionospheric propagation.

The critical frequency of the F-layer is measured near real-time by ionosonde stations. Please take a look at them, they are very informative. The following link is from an ionosonde in Belgium, but there are several in your area as well:

Is your interest driven by radio wave propagation issues, or earth science interest?

PLL is usually implemented d in analog domain but digital locked loop also exist that do the same in discrete time domain. however the most useful techniques for your case would be frequency recovery technique in addition to clock and phase recovery. the book written by Mengali is great reference in synchronization technique.

A couple of days ago an article about SDR was published.

The device costs 40$ only.

Some handicraft pages:

Regards,

Joachim

Dear Viky,

A communication link consists of a transmitter , a receiver and a communication medium. Every medium has the suitable signal energy form to propagate easily in it.

Good electricity conductors such as metals are conveyor of electricity.Therefore transmission lines are made from metallic conductors like copper and aluminium.It is not practical to connect the transmitters and receivers in underwater by transmission line.

Therefore one uses the suitable wireless system for under ware communication.

Basically there are two basic wave types, the acoustic waves and the electromagnetic waves. Sea water is salty and therefore good conducting as Dr Garry mentioned. Consequently it attenuates the electromagnetic waves and this attenuation increase as the frequency increases. Only low frequency electromagnetic waves are capable to propagate an appreciable distance before it gets undetectable.Therefore the radio wave under sea water communication is restricted to very low frequency waves with very small band width and consequently very low data rates. Newly, short distance under water optical communication links are developed operating in the wavelength range from 0.4 to 0.55 micrometers.They can be considered also wireless electromagnetic wave communication.

As a medium the sea water is suitable as a fluid is suitable for acoustic wave propagation. Therefore, the under water communication systems are normally

based on acoustic wave transmission. Here piezo electric transducers are used to convert the electrical signal into acoustic waves and vice verse. The rest of the system remains the same.For more details please go to the link: www.tr.ietejournals.org/article.asp?issn=0256-4602;year=2012

I agree with Johannes that this "pure" view is not very practical. SDR was always envisioned as a slow evolution from completely unconfigurable systems (i.e., hardware-defined systems) to reconfigurable systems (defined by software which may be uploaded to effect different personalities). For instance, see Mitola 99 "Software Radio Architecture: A Mathematical Perspective", the block diagram in that work is far more complex than what you are calling an SDR. I would suggest that at today's processing capabilities and expectations of extremely (or even moderately) high data rates from consumers the ultimate goal that you describe is not in reach. But this thing you speak of is not the one-and-only definition of SDR.

To me, the advantage of an SDR is its reconfigurability and its flexibility. Why else would you want one? So, here's my question to you. If you have a truly reconfigurable radio (say something even better than the prototyping platforms on the market today) that can be reprogrammed (by a host computer or its own "intelligence") to modify its carrier frequency, data rate, modulation format, etc... Albeit based on some "custom" but reprogrammable hardware. What is the difference whether we call it massively reconfigurable hardware-defined radio (MRHDR?) or software-defined radio (SDR)? Aren't the end goals of both the same? What more does the platform you describe offer us above and beyond this reconfigurability? I would argue that the amount of software and programmable hardware that goes into platforms currently available merits the name software-defined radio as it is the software that gives the radio its definition (operating parameters, signal characteristics, etc). Most of the SDR research that interests me would not be classified as SDR by your definition. I think this definition is too narrow. After all, I would suggest that our personal computers are software-defined even though they may have custom hardware attached (e.g., high performance video cards).