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ABSTRACT
The concept of 2-D barcodes is of great relevance for use in wireless data transmission between handheld electronic devices. In a typical setup, any file on a cell phone, for example, can be transferred to a second cell phone through a series of images on the LCD which are then captured and decoded through the camera of the second cell phone. In this study, a new approach for data modulation in 2-D barcodes is introduced, and its performance is evaluated in comparison to other standard methods of barcode modulation. In this new approach, orthogonal frequency-division multiplexing (OFDM) modulation is used together with differential phase shift keying (DPSK) over adjacent frequency domain elements. A specific aim of this study is to establish a system that is proven tolerant to camera movements, picture blur, and light leakage within neighboring pixels of an LCD. Index Terms—Barcode, data transfer, differential phase shift keying, orthogonal frequency-division multiplexing (OFDM) modulation
INTRODUCTION
1.1 Introductions:
Barcodes have played a great role in facilitating numerous identification processes since their invention in 1952 [1]. In fact barcode is a simple and cost-effective method of storing machine readable digital data on paper or product packages. As pressing needs to transfer even more data faster and with high reliability have emerged, there have been many improvements that were made on the original barcode design. Invention of two dimensional (2D) or matrix barcodes opened a new front for these cost-effective codes and their application in more complex data transfer scenarios like storing contact information, URLs among other things, in which QR codes [2] have become increasingly popular. A comparison of 2D barcode performance in camera phone applications can be found in [3].
Much of the efforts in matrix barcode development have been dedicated to barcodes displayed on a piece of paper as that is the way they are normally used. With the replacement of books with tablets and e-Book readers one could contemplate that replacement of the paper with LCD may open another promising front for broader applications of 2D barcodes as a mean of data transfer. Moreover unlike the static paper, the LCD may display time-varying barcodes for the eventual transfer of streams of data to the receiving electronic device(s)
This idea has been implemented in [4] where transmission of data between two cell phones through a series of 2D QR codes is studied, achieving bit rates of under 10 kbps for state of the art mobile devices. Later the idea was further developed in [5] in which a computer monitor and a digital camera are used for transmission and reception with bit rates of more than 14 Mbps achieved in docked transmitter and receiver conditions over distances of up to 4 meters. However, this rate drops to just over 2 Mbps when the distance is increased to 14 meters. The superior performance of the later implementation is achieved using a more effective modulation and coding scheme for mitigation of image blur and pixel to pixel light leakage. The general idea is to use the inverse Fourier transform (IFT) of data like OFDM to modulate LCD pixels. While image blur and light leakage greatly reduce the performance of QR decoders they have a limited effect on OFDM modulation. Furthermore their performance degradation is con fined to known portions of the decoded data. This prior knowledge on non-uniform error probability may be used for adaptive error correction coding based on data region as in [5]. There is an increasing interest in design and implementation of LCD-Camera based communication systems as indicated in [6]–[8]. This would require additional investigations in determining optimal modulation and demodulation schemes for this type of innovative communications medium.
The OFDM modulation uses orthogonal frequency subcarriers to transfer data and can con fine image blur, which is essentially a low pass filter, to high frequency components such that low frequency data bits are transmitted intact. This method requires high phase coherency to detect the data bits correctly. The current study extends this idea through additional modifications on the modulation scheme in a way to mitigate LCD - camera relative movements during the capture of a single frame , which results in motion blur it sort ion on the captured images . This kind of distortions would be detailed later severely degrades the performance of Quadrature Phase Shift Keying (QPSK) modulated OFDM signals.
The required movement tolerance is achieved by putting data in phase differences of adjacent frequency components leading to a DPSK-OFDM scheme which would be called simply the DPSK method throughout this study. Observing that any phase distortion due to motion blur would affect neighboring frequency components negligibly, data may be transmitted reliably even in the vicinity of high LCD, camera relative motion. A diagram of the system envisioned is shown in Fig. 2. This method also eliminates the channel estimation requirements resulting in lower processing power.
To maximize data transmission rate, one should consider extracting maximum data from a single image shown on an LCD and then increase the rate at which consecutive frames will be decoded. In consideration of this issue, any method that is introduced should efficiently utilize the available bandwidth considering motion distortions.
Previous studies have demonstrated the feasibility of such systems and have addressed the effects of single distortions like linear misalignment [9], defocus blur [10] and vignetting [11] on the modulation methods under consideration, but they have not provided a comparative assessment of these systems in a controlled environment. Moreover, no comparisons were made in case of LCD camera motions which greatly affect the performance of the system in applications that involve handheld camera-phone receivers. As a consequence, this study introduces DPSK-OFDM as a means of mitigating LCD camera motion distortions and sets a series of simulations based on mathematical modeling for blur and motion on the received images in a way that the distortion would be the same for PAM (Pulse Amplitude Modulation), QPSK-OFDM and DPSK-OFDM modulations. As a result, a reliable comparison can be made between these major modulation methods regardless of other parameters affecting the performance of such practical systems.
BACKGROUND
Two-dimensional barcodes have proven to be an effective method of labelling where central databases are infeasible and physical surface area is limited. The potential roles of these 2-D barcodes have certainly not been exhausted and there are several promising applications emerging with the ever-expanding digital world.
Camera phones encompass one of the newest domains entered by the barcode, as well as one of the most exciting. Several recent press releases indicate the growing popularity of this application [6, 7, 8, 9, 10, 11]. In April, 2007, BBC News presented the High Capacity Color Barcode (HCCB) for cell phone scanning, and indicated that the symbol would appear on DVDs within a year [6]. Fujitsu recently introduced an encoding technology that embeds data invisibly into a picture to be decoded specifically by mobile phones [10]. This was in response to aversion toward the obtrusive appearance of Quick Response (QR) symbols on advertisements. QR Code and Data Matrix decoders for cell phones are increasing in popularity, and a high percentage of Japanese people have used QR Codes for a cell phone application.
In order to capitalize on the barcode possibilities presented through personal wireless devices, such as cell phones and blackberries, many considerations must be made. Although a high data-density is appealing to corporations looking to advertise, the user experience must be taken into account. Cell phone processor sizes must be considered, as well as the distortion presented by capturing the barcode with the cell phone camera. In order to create a barcode system that is practical for use with a cell phone, it is imperative that the probability of decoding failure is low so that the consumer finds it easy and enjoyable to use.
Some recent reviews of barcode scanning and decoding with cell phones have been disappointing. It might be worth considering camera phone specifics when designing a symbology, as opposed to forcing an ill-suited symbology into the desired application. Although the HCCB shows promise in this domain and claims to be suited to camera phone applications, its data-density is inferior to some other symbologies despite its use of eight different colours.
Perhaps a combination of spatially bandwidth-efficient coding, the use of colour, and consideration to cell phone-specific applications could yield a superior code for this particular function. Investigations into this area are worthwhile, especially since the processing power of cell phones has been increasing, and will continue to do so.
There are other applications and potential symbology improvements. If 2-D barcode systems are to be adopted by industries to provide a simple and convenient interface between the paper and digital domains for their consumers, aesthetics will play a role. The ideal barcode is as flexible in size, shape and colour as possible. This will allow it to blend discreetly into packaging, advertisements, or company logos. Fixed architectures, fiducials, and other position locator markings lessen the appeal of most current symbologies.
There are many possibilities for 2-D barcodes in the near future. A barcode designed judiciously to have a high data-density, a reasonable decoding complexity, a flexible size and appearance, and sufficient robustness to noise and distortion has the potential to take barcodes from their specialized functions in industry to a universally employed interface between printed and digital domains.
The design of a data-dense, robust, flexible, and easily decodable 2-D barcode will allow barcode systems to penetrate new markets and succeed in new applications. Given the technology available, there are no obvious obstacles to achieving such a code, and therefore the R&D process should not be delayed. Before delving into a new barcode design, it is worth looking at current symbologies and identifying their features and limitations.
2.1 Symbology Background
The first barcode patent was issued to Joseph Woodland and Bernard Silver in 1952 [12, 13]. Since their major debut in grocery stores as the distinguished Universal Product Code (UPC), barcodes have evolved significantly and are prominent in our world today.
Barcode symbology refers to the mapping between the message and the barcode. The first barcodes employed one-dimensional symbologies, meaning that encoding is done in only one spatial dimension (along one axis). Two-dimensional symbologies revolutionized barcode technology by also encoding data in the second dimension of the surface. Today, further advancements are being made to take 2D symbologies away from their traditional encoding schemes in order to increase data-density and enhance performance.
2.1.1 One-Dimensional/Linear Symbologies
There are several distinguished linear barcodes in addition to the ubiquitous UPC, such as the well-known International Standard Book Number (ISBN) used to uniquely identify each edition of every published book and book-like product [14].
As illustrated in Figure 2.1, one-dimensional barcodes encode data along the horizontal axis through the use of bars and spaces. The specifications include the actual encoding of digits as well as the marking of bars and spaces. One-dimensional barcodes can be categorized as being discrete or continuous, as well as having two bar widths or many bar widths [15].
Continuous symbologies have characters adjoined, with one character ending in a bar and the next beginning in a space, or vice versa. Discrete symbologies use characters that begin and end with bars. The inter-character space is generally ignored.
Two-width symbologies have one designated narrow bar width and one wide bar width. The widths are specified in relative quantities, usually with the wide width being two or three times greater than the narrow, so there is no dependency on the absolute measurements. Many-width symbologies use bars and spaces that are all multiples of a specified width, called the module of the code.
One-dimensional barcodes are read using optical scanners, often called barcode readers. The scanners are either hand-held or fixed-mount. Handheld scanners are used for stationary items, while fixed-mount scanners require that the item be physically passed by the scanner. This is usually done by hand in retail applications and by conveyor belt in industrial applications [16]. In general, both handheld and fixed-mount scanners employ either a laser or a CCD (charged-coupled device) imager.
Laser scanners were the first type of barcode reader to be utilized. They use a laser diode to create an infrared beam which is spread in an arc parallel to the barcode by a rapidly rotating mirror. A photodiode is then employed to measure the intensity of the light reflected back from the barcode surface. More sophisticated scanners often use revolving polygons or oscillating mirrors to enhance performance. The optimal scanning distance for laser scanners is typically 6-12 inches, but can range up to 35 feet for certain reflective barcodes [1,13].
CCD scanners use a stationary flood of light, usually LEDs (light emitting diodes), to re flect the symbol image back onto an array of photosensors. The optimal scanning distance usually ranges from physical contact to six inches. CCD scanners are generally less expen sive than laser scanners and have a durability advantage, primarily because they contain no moving parts. As a result, CCD imagers are surpassing laser scanners as the preferred technology for reading linear barcodes.
Linear barcodes are used extensively in libraries, grocery stores, and almost all com mercial environments. Their role of efficiently linking an item to its location in a database is expected to continue despite significant advancements in barcode symbologies. Higher density, two-dimensional barcodes are generally unnecessary for applications where linear barcodes currently dominate. However, RFID (Radio Frequency Identification) tags may offer advantages over barcodes to manufacturers in such domains.
If linear barcode systems are replaced in retail venues, RFID tags would probably be a more appropriate substitute than two-dimensional barcodes. RFID tags (also known as transponders) do not require a direct line of sight for reading and may be read through hard material such as book covers or other packaging material. Each tag can uniquely identify the object to which it is attached, even if that object is one of a multitude of identical items. However, RFID tags are more costly than barcodes and raise privacy concerns [17].
Linear barcodes play a well-established role in industry that is not currently threatened by higher density barcodes. However, there are a multitude of other applications for which linear barcodes are insufficient because a central database is simply not feasible, or surface area is limited.
2.1.2 Two-Dimensional Barcodes
In order to meet the demand for a higher data-density barcode system, two-dimensional symbologies were developed. The ability to encode a portable database in a limited spatial area has allowed barcodes to prevail in applications originally prohibited by the linear symbology. The health care industry benefited by being able to label unit-dose packages, with the labelling of other medicines and tools to follow. The electronics industry also began using two-dimensional barcodes to label small parts. Several other industries have followed with a variety of applications.
The two-dimensional concept was initiated in 1984 when the Automotive Industry Action Group introduced a standard for shipping and identification labels which consisted of four Code 39 barcodes (a linear symbology) stacked on top of each other. Then in 1988, Code 49 was introduced by the Intermec Corporation to become the first truly two-dimensional barcode on the market. Like the stacked Code 39 barcode, Code 49 also used the idea of layering linear barcodes along the vertical axis, as can be seen in Figure 2.1 [2, 18].
Several different two-dimensional barcodes have been introduced since Code 49. For the most part, they can be categorized as having either a stacked or a matrix symbology. However, many barcodes do not fit into either of these categories, particularly those most recently developed.
2.2 Stacked Symbologies
A stacked symbology is the most primitive of all possible two-dimensional schemes, and perhaps the most intuitive when starting with a linear barcode system. Several linear barcodes of a given symbology are truncated and then layered vertically to create the stacked symbology. A much higher data-density than the linear code is achieved at the price of less vertical redundancy.
Stacked barcodes were optimized to be read using a laser scanner in which the laser beam is swept several times horizontally as it makes its way down the barcode vertically. Certain symbologies, such as Codablock, allow the barcode to be read by a linear barcode reader (a standard moving beam laser) with very little modification. CCD imagers are also used to read stacked-symbology barcodes. The scanning requirements and constraints are specific to the code symbology.
Many stacked-symbology barcodes continue to be used in various industries, such as Code 16K and Codablock (Figure 2.1) in the health care industry, and PDF 417 (Figure 2.1) in transportation, personal identification and inventory management domains [1, 19]. However, despite its successes, more efficient encoding methods have made the stacking technique obsolete.
2.3 Matrix Symbologies
Matrix codes encode data through the positioning of equal-dimension spots within a matrix (dark spots on a light surface). The symbology usually includes patterns that indicate the orientation of the barcode, and often convey the size and printing density of the barcode as well. CCD imagers and camera capture devices are used to scan matrix barcodes.
There are several matrix symbologies in the public domain, as well as many proprietary ones. United Parcel Service (UPS) developed its own well-known matrix symbology, Maxicode (or UPSCode), in 1992 to label and track packages. Maxicode is made up of interlocking hexagons and includes a central bull’s-eye marking to aid in acquisition (see Figure 2.1). The code requires a very high resolution printer, but can be read by a CCD scanner or camera when even up to 25% of the symbol is destroyed.
Matrix symbologies are often created with specific practical constraints in mind. For instance, the Aztec Code was designed to be easily printed and decoded, the QR Code was designed for rapid reading using CCD array cameras, and the Data Matrix was created to achieve a very high data-density (see Figures 2.3 and 2.4). As a result, matrix symbologies tend to be more application-specific than stacked symbologies.
Matrix symbologies generally offer many advantages over stacked symbologies, primarily because they use space more efficiently and scatter redundancy to increase robustness. However, the drawbacks of matrix codes are prompting the creation of symbologies that diverge from the traditional matrix model. Although most new symbologies do not fit either the stacked or matrix definitions, many do resemble matrix codes in some way, and often employ many of the same concepts.
2.4 Other Two-Dimensional Symbologies
Several 2-D barcodes cannot be categorized as having either a stacked or a matrix symbology. DataGlyphs, for instance, are made up of forward and backward slashes (/ and \), representing binary ‘0’s and ‘1’s respectively (Figures 2.6 and 2.7). INTACTA.CODE is a propriety code that converts binary files and software into a very high-density machine-readable symbol of scattered dots (Figure 2.2). Advancements in computer imaging techniques and devices have made coloured barcodes more feasible for a variety of applications. As a result, some barcodes use colour to increase data-density, such as the HCCB (High Capacity Color Barcode, seen in Figure 2.5), the Ultracode (Figure 2.1), and the HueCode.
The newest barcode symbologies offer more unique features and are difficult to categorize. Developments continue as demands on current barcode systems grow and new barcode applications emerge. There are advantages and drawbacks to each barcode design, and symbologies are usually designed for specific requirements and constraints. There has been significant progress in recent years, and development is expected to continue in the barcode symbology domain [9].
2.5 Specifics of Notable Two-Dimensional Barcodes
It is worth examining some of the more notable 2-D barcodes. Whether they have gained popularity in certain fields of use, or offer unique features to the user, they can give insight into what has already been accomplished as well as potential improvements for the future. Six significant 2-D symbologies are briefly described and then compared.
2.5.1 INTACTA.CODE
INTACTA.CODE is a proprietary code developed by INTACTA Technologies, Inc. that converts binary files into a graphical representation, thus securing information over electronic media and in printed form. The development of INTACTA.CODE was initiated by the defence industry, where privacy is of critical importance. In addition to security, INTACTA Technologies places emphasis on bandwidth efficiency (to efficiently increase data-density) and error-correction abilities, while being easy and practical to adopt for various applications.
INTACTA.CODE looks like a random arrangement of dots (Figure 2.2). Each byte of information contained in the symbol is represented by a small pattern of black and white dots. Prior to encoding, the data is compressed and encrypted by the INTACTA software, with a high level of flexibility left to the user. The barcode can then be created in a printable or a digital format. Also, because the code is not based on a fixed architecture, it can be formed into any desired continuous shape.
INTACTA.CODE can be read by any off-the-shelf scanner and is decoded by proprietary software. The data-density depends on the printing and scanning resolutions. INTACTA.CODE achieves 1000 bytes/inch 2 (1240 bits/cm 2) at 300 dpi resolution and 3800 bytes/inch 2 (4712 bits/cm 2) at 600 dpi resolution, assuming equal printing and scanning resolutions. Intacta Technologies has indicated that a colour INTACTA.CODE is also possible, but such a symbol has yet to be presented publicly. See [20, 21, 22] for more information.
2.5.2 Data Matrix
As its name suggests, Data Matrix employs a matrix symbology. It was patented in 1991 and achieves a high data-density compared to other barcodes of its time. The Data Matrix symbol is also variable in size, giving it a significant advantage over several fixed-architecture barcode symbols. A Data Matrix symbol consists of a matrix of equal-sized squares, as illustrated in Figure 2.3. It is read by CCD camera / scanner.
The perimeter of the Data Matrix symbol indicates the density of data contained within the matrix. The product of the number of light squares and dark squares of the first and second sides correspond to the number of bits of information contained in the symbol, while the solid dark lines on the third and fourth sides indicate the height, length and area of the symbol. Because of the information contained in the perimeter, the Data Matrix code can be scanned from any orientation, as well as at an angle using a camera capture device.
Instead of representing individual bits by individual light/dark squares, the Data Matrix symbology compresses the input data by defining a maximum range of characters that may appear in an input string, and removes redundancy to reduce the number of squares required to represent that string. For this reason, the compression process depends on the type of input character anticipated.
Robustness is increased by scattering redundant data throughout the symbol. This is accomplished by randomly positioning redundant cells (squares in the symbol) as far as possible from the root cell encoded. The user can specify the redundancy level (up to 400%). Convolutional coding was originally applied, but Reed-Solomon error correction algorithms are now used, allowing the Data Matrix barcode to be decoded when up to 60% of the symbol is damaged.
The data-density achieved by a Data Matrix symbol depends on the size of the symbol, the size of the cells (which will depend on the scanning resolution), and the amount of redundancy included. In theory, the symbol can store 500 characters in a square milli-inch. This is, of course, impractical when taking printing and scanning resolutions into account. More realistically, using 600 dpi and 4 dots per module, a data-density of approximately 1838 bits/cm 2 is achieved (see Appendix A).
2.5.3 HCCB (High Capacity Color Barcode)
The HCCB (High Capacity Color Barcode) is one of the newest barcode symbologies to be introduced. It is a proprietary code by Microsoft Corp. that is awaiting a patent to be issued in the United States. By using colour, the HCCB achieves a high data density and has been designed with consumer cell phone applications in mind.
Triangular symbols are arranged compactly throughout the symbol, as in Figure 2.5. The triangles are separated by white spacing that serves to reduce aliasing effects and other distortions. A similar symbol structure using geometric shapes other than triangles is also possible for the HCCB, but triangles are currently being used because they are more efficiently packed.
The HCCB includes CRC (Cyclic Redundancy Check) error-detection and Reed-Solomon coding for error-correction. A reference colour palette is included in the HCCB symbol to allow for a weighted adjustment that reflects or compensates for variations in dynamic range perceived by the camera/scanning device. Should the reference palette on the barcode symbol be damaged, the necessary adjustments can still be made based on history or previously scanned palette colour values (Microsoft claims this technique has been proven to be empirically reliable [25]).
Data-density varies in relation to the colour scheme chosen. Microsoft offers its HCCB in black and white, with four different colours, and with eight different colours. Other schemes, such as grayscale, are also possible and may be available in the future. Using the eight-colour design at 600 dpi resolution, a data-density of 2000 bytes/inch 2 can be achieved (2480 bits/cm 2).
The HHCB can be read in a variety of ways, including using a flat-bed scanner, a business card reader scanner, a digital camera, a video camera, or a Web cam. Microsoft is promoting potential cell phone applications, highlighting that the HCCB outperforms QR Code and Data Matrix formats for cell phone scanning and decoding.
Microsoft Corp. and the International Standard Audiovisual Number International Agency (ISAN-IA) announced an agreement whereby ISAN-IA has licensed the HCCB to assist in the identification of commercial audiovisual works such as motion pictures, video games, broadcasts, digital video recordings and other media. The barcode is expected to start appearing on DVDs and Xbox games in the near future [29, 30].
DPSK-OFDM AND PSK-OFDM
The first OFDM scheme introduced by 1966’s.In this OFDM data is transmitted in parallel on multiple carriers that overlap in frequency. OFDM also known as multi carrier or multi tone modulation scheme. Previously we are done techniques TDMA, FDMA, CDMA.
3.1 Frequency division multiple accesses is a channel accesses method used in multiple access channelization protocols. It gives an individual user allocation of one or several frequency bands or channels or slots. (Frequency division multiple access, possibly the most straightforward, in which every user device uses its own frequency channel. This method was used in the first generation analog systems).
3.2 Time division multiple accesses are a channel access method for shared medium networks. It allows several users to share the same frequency channel by dividing the signal into different time slots so the user transmits in rapid succession one by one but each using its own time slot. (Time division multiple access, in which a radio channel is divided in time slots, and use devices use their allocated time slots. In fact TDMA systems are often hybrid FDMA as well as multiple channels are used, most 2G systems were TDMA).
3.3 Code division multiple accesses used in 2ND and 3RD generation wireless communications. It is a form of multiplexing which allows several signals to occupy a single transmission channel, optimizing the use of available bandwidth. (Code division multiple access, in which orthogonal (or pseudo orthogonal) codes are used to differentiate user devices. CDMA is very spectrum efficient, and was used by 3G standards. There are several approaches to achieve CDMA, such as frequency hopping (FH-CDMA) or direct spreading (DS-CDMA)
These are the main multiple access techniques, but subtle extensions and combinations can be devised to obtain more efficient schemes i.e. orthogonal frequency division multiplexing.
3.4 What is OFDM?
Data transmitted in parallel to multiple carries that overlap in frequency transmission and also orthogonal to each other or OFDM is a frequency-division multiplexing (FDM) scheme used as a digital multi-carrier modulation method. A large number of closely spaced orthogonal sub-carrier signals are used to carry data on several parallel data streams or channels.
Orthogonal Frequency Division Multiplexing (OFDM) has been attracting substantial attention due to its excellent performance under severe channel condition. The rapidly growing application of OFDM includes Wi-MAX, DVB/DAB and 4G wireless systems.
3.5 Orthogonal frequency division multiplexing widely used in wireless communication system. It can be viewed as a either a modulation technique (viewed by the relation between input and output signal) or multiplex technique (viewed by the output signal which is linear sum of the modulated signal) and it does not required bandwidth and it is a multi carrier transmission technique, which divides the available spectrums (carriers) into many sub carriers each one being modulated by a data rate (speed) streams. OFDM strictly relation between the carriers and these carriers are orthogonal to each other and each subcarrier can be packed tightly.
Frequency division multiple accesses is a channel accesses method used in multiple access channelization protocols.FDM standards for Frequency division multiplexing and it have no special relation between the available carrier’s frequencies. In FDM signals are multiple transmitters and transmitting simultaneously over multiple frequencies. Each sub carrier is modulated separately by different data stream and a guard band is placed between subcarrier to avoid signal overlap example broadcast radio or FDM presents guard band or spacing and the guard band inserted to be avoiding adjacent channel interference. In this signals are sent in different directions of channels: It does not require the interference and most widely used in radio transmissions.
The Advantages of OFDM Very easy and efficient in dealing with multi-path and Robust again narrow-band interference. The Disadvantages of OFDM Sensitive to frequency offset and phase noise and Peak-to-average problem reduces the power efficiency of RF amplifier at the transmitter.
Orthogonality means, it allows the sub carriers, which are orthogonal to each other, meaning that cross talk between co-channels is eliminated and inter-carrier guard bands are not required. This greatly simplifies the design of both the transmitter and receiver, unlike conventional FDM as shown below; a separate filter for each sub channel is not required.
Relation between FDM and OFDM:
OFDM introduces the concept of allocating several channels with in the limited spectral width compared to frequency division multiplexing. The relation between FDM and OFDM uses multiple subcarriers. But they are closely spaced to each other without causing interference and removing guard bands. Individually in OFDM subcarriers are orthogonal to each other, thus it requires no band gap it improves spectral efficiency. In FDM band gap is required to avoid inter channel interference, which reduce the overall spectral efficiency.
OFDM is a multicarrier modulation scheme that transmits data greater than a number of orthogonal subcarriers.FDM transmission uses only a single carrier modulation with all data to be sent in single carrier.OFDM breaks the data to be sent into small parts, allocating each sub data stream into a sub carrier stream and the data to be sent in a parallel direction of orthogonal subcarrier.
3.8 For example of FDM and OFDM:
OFDM is a multi carrier modulation scheme that transmits data greater than a number of orthogonal sub carriers. Suppose we are taking two trucks to carry some goods and in these one truck is FDM it is single carrier transmission technique with all the data to be sent in a single carrier transmission scheme and another truck is the OFDM it is a multi carrier transmission scheme in this OFDM breaks the data to be sent into the small chunks, and allocating each sub data stream into a multiple sub carrier stream and the data to be sent in a parallel direction of orthogonal subcarrier.
Similarly like that one tap water instrument (single hole and transmitting data in single direction) and shower gel instrument (multiple holes and data transmitting in parallel direction .If one hole is blocked then the data is transmitting continue to another blocks. Here data means flow of water) both are example of FDM and OFDM schemes.