Performance analysis of negative group delay network using MIMO technique

ABSTRACT


INTRODUCTION
Since 1960s, wireless systems have promptly mounting segments with the potential for making available, swift and super information exchange among convenient devices placed somewhere in the world.The remarkable growth of wireless communication technology is because of a union of numerous aspects.Primarily, the requirement of the wireless connection has increased highly.Secondly, the spectacular advancement of VLSI machinery has activated low-power and compact implementing of complex code and signal processing.Thirdly, 2 nd generation wireless communication standards, as in GSM, cause it achievable to broadcast voice with small volume of digital data.In addition, a 3 rd generation of wireless systems has given clienteles higher service quality which accomplishes greater capacity and spectral efficiency [1].
Prospective applications activated by wireless systems consist of multimedia facilities on cellular phones, stylish homes, computerized highway systems, video chatting and self-directed sensor networks.On the other hand, there have been dual major technological challenges in sustaining these appliances: first challenge includes a fading occurrence, deviation time of the channel in consequence of a small-scale outcome of multipath fading along with large-scale influence as in pass loss by remote attenuation and obstacles shadowing.Moreover, as wireless sender and receiver require air communication with noteworthy interference TELKOMNIKA Telecommun Comput El Control  Performance analysis of negative group delay network using MIMO technique (Yaqeen S. Mezaal) 2573 among them.All challenges have been mainly due to restricted accessibility of radio frequency range and the complex time-varying wireless regulating.
At present, a main objective in wireless engineering is for upturning information rate and developing transmission dependability.Specifically, owing to the growing demand for superior bit rates, better-quality service quality, less faults, upper network capability and user coverage calls for inventive techniques which enhance spectral effectiveness and channel reliability, more and more wireless communication technologies have been initiated, like MIMO techniques [2].In 1998, Alamouti built up diversity design using dual antennas in the transmit side and single antenna in the receive end.This design offers the identical diversity order like the maximal-ratio combining (MRC) in a receiver end, with single sending antenna and dual receiving antennas.Bandwidth extension in this design hasn't required.An entire coming response from receiving to sending antennas and its calculation complexity level have been identical to MRC [3].Many categories of NGD network using RLC resonators were, in theory and experiments, proven in reported papers in [4][5][6].Nevertheless, no one of them had employed transmission-type toplogy for NGD network by means of the parallel RLC resonator with a distributed transmission line due to an application inconveniency.Wilzeck et al. [7], proposed MIMO test-bed that uses two sending antennas and four receiving antennas receiver in "offline" mode, in which pre-processed data has been sent over-air and logged for upcoming processing.The receiving system permits 512 Mbytes of memory for every receive antenna and maximum sampling frequency of 100 MHz, which causes 2.68 seconds of logging time with 14-bit resolution.The test-bed has been in relation to Sundance's modular digital signal processing platform and plug-in radio frequency constituents produced through Mini-Circuits.Besides, bandpass filters using microstrip technique at 2.4 GHz resonant frequency have been used to prevent image bands and enhance the operation of adopted system.Lozano and Jindal [8], offered MIMO wireless network that has diversity principles.
This wireless system is based on the trade-off between spatial multiplexing and transmit antenna diversity.Bhatnagar et al. [9], showed MIMO OFDM wireless network using space time block coding (STBC) throughout Rayleigh channels by means of 2PSK as well as 4PSK modulations to conquer sub-channel interfering.Simulated output graphs showed that there is reduction in bit error rate amounts as SNR raises.On the other hand, the system throughput increases as SNR decreases.Premnath et al. [10], proposed a new rapid algorithm for antenna selection in wireless MIMO systems.This technique does comparable capacity as the most advantageous selection method and the rapid processing at more lessened computational costs.The applied uncomplicated G-circles process decreases the complication notably with a rational performance loss.It can be as well efficiently organized in correlation matrix-based on antenna selections.Multi band antennas for wireless systems have been presented in [11][12][13][14][15][16][17][18].These devices are very important to operate in separated strategic bands for front ends of wireless systems especially for MIMO configurations.In this paper, the MIMO antenna configurations for IEEE802.11model uses new microstrip slotted patch antenna with multiple interesting bands and significant NGD values.The return loss of the proposed antenna is suitable to be adopted with MIMO wireless configuration.By the influence of this antenna, the corresponding BER has been investigated using MATLAB simulator.

SPACE-TIME BLOCK CODES
Assume a wireless configuration has N sending antennas and M receiving antennas in a flat fading channel with a propagation gain l mn h , .The parameter l mn h , is an independent complex Gaussian with variance 0.5 for every element in Rayleigh distributed random variable.Here, n, m, and l are indicators of sending antenna, receiving antenna and time, correspondingly.In STBC communication system, the code can be described by C matrix and STBC period by L. Supposing T is the symbol interval, a collected signal in a receive antenna m under lT time can be determined by [2,19,20]: , represents the (l,n) part of the L by N code matrix C, while  , belongs to additive noise with variance  2 and zero-mean.In the case of quasi-static channel, the time index l in l mn h , is feasibly misplaced.Signify (⋅)  , (⋅) * and (⋅)  as a Hermitian transpose, a complex conjugate and a transpose, correspondingly.Through accumulating the vector form of received signal, as shown in (1) for quasi-static channel is expressed as: the (m,n) element mn h , and an L by M noise matrix.It has been hard for implementing signal processing procedures to the matrix depiction in (2), because a code matrix C has not stated as a linear arrangement of STBC input symbols.Additionally, for not quasi-static channels, it is not possible to convert as shown in (1) into (2).Therefore, there is necessity to make an all-purpose expression form irrespective of code constitution or channel state.With the intention of applying signal processing techniques, linear superposition is required, as in (3); Here, r indicates the LM by 1 received signal vector, z has identified as the K by 1 sent signal vector [1 ⋯   ]  ,  ̄ is the LM by K channel matrix, and ̄ points to the LM by 1 noise vector.Various STBC schemes are feasibly changed into the linear superposition structure.A code matrix C used for Alamouti scheme [3] can be written as: The code is transformed into the linear superposition representation (LSR) in this following manner.Through determining the conjugating of 2 nd half of the received signal, the LSR for Alamouti system has described by: where   , l n h , , and   stand for M by 1 column vectors at time lT and have expressed as  and [  1,  2, ⋯  , ]  , correspondingly.
For quasi-static channels, the best possible discovery for the Alamouti method can be done by only multiplying the vector ̄ by  ̄ and adjusting the symbol by symbol detector.A complete Maximum Likelihood (ML) search has denoted as the extensive exploration for equation solution, ‖̄−  ̄‖ 2 , through inspection every probable sets of sent symbols.However, for wide-ranging STBC systems, it is not viable to generate a complex LSR for (3).For instance, for N=4 antennas configurations at a rate of 3/4, we assume C matrix [21] as: This code matrix is not convertible to a complex LSR as achieved in the Alamouti code.But, if real and imaginary parts matrix facets are defined separately, the collected vector can be written in a real LSR.Ordinarily, by separating the real and imaginary components, each block code can be described.This is known as the lattice version.

LATTICE VERTION FOR STBC SCHEMES
A regular form of the lattice (higher orders) version for STBC can be constructed by dividing C matrix into dual components that are defined as  ̃= [    ] where   and   refer to real and imaginary elements of the vector or matrix, correspondingly.If   =   +   has been considered, presume that the (l,n) constituent of C represents  , =  1   +  2   , in which 1 c and 2 c stand for scalar constants.After that, the lth row vector of   and   has been symbolized by where .By resembling the depiction lattice to transform a complex channel matrix equation into real lattice channel matrix  ̃ as stated in [14], the formation of  ̃ of the adapted code matrix  ̃ will be: A different case we take in the consideration here, is the code, where some   's are joint in (l,n) element of C in the preservative form.Namely,   comes into view more than once in one row of C.This type of codes can be defined by adopting the linear superposition criteria.Accordingly, the code matrix will be [14]:

]
A lattice channel matrix can be expressed as:

~h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h h
In the circumstances of the quasi-static channel response, the equivalent channel matrix has been orthogonal in a case of orthogonal code matrix [19].Consequently, a transpose of real lattice channel matrix  ̃ belongs to a matched filter.The symbol by symbol ML detection has been in a highly advantageous case and optimal after matched filtering.The outcome of the matched filtering for a symbol   has been: where n ˆ represents a new term of additive noise with mean equals to 0 and variance equals to , and  is the channel response power.However, more in-depth STBC encoding and decoding information with the various number of transceiver antennas have given in [20][21][22][23][24][25].

MIMO SYSTEM MODEL OF IEEE 802.11
Alamouti scheme has been employed extensively in MIMO wireless systems.The typical adopted MIMO block diagram uses STBC signal processing at transmit and receive antennas as in Figure 1.We used applied wave research (AWR) electromagnetic package in designing and simulation of that MIMO antenna.This simulation software package provides schematic circuit technology with good performance in accuracy, capacity, convergence and speed.The microstrip antenna with uniform geometrical slot provides good performance of the antenna frequency response using dual via ports.
This MIMO antenna, as depicted in Figure 2, has been modelled based on FR4 substrate with dielectric constant of 4.4 and h of 1.6 mm.Dual via ports are positioned in the main microstrip resonator.The projected antenna substrate dimensions have overall of 31x31 mm 2 .The consequent S11 (return loss) response has clarified in Figure 3.The S11 response in this graph has band frequencies of 2.4 GHz, 4.4 GHz, and 5.54 GHz.The subsequent input reflection values are 20.1, 18, and 15.2 dB for each band respectively, while the bandwidth ranges are 2.389-2.42,4.314-4.47and 5.545-5.61GHz for the same band frequencies respectively.The new MIMO antenna has compact size and worthy frequency responses and multiple service bands that have been looked-for features for many MIMO wireless configurations as perceived by Figure 3. Table 1 explains the dimensions of proposed MIMO antenna.With the intention of getting close by the angle response of S11 scattering parameter of the suggested microstrip MIMO antenna, simulation phase response at band resonant frequencies is depicted in Figure 4.This graph shows that the proposed antenna has good phase response linearity within 1 to 6 GHz sweeping frequency range.In Figure 5, group delay response of projected antenna has been presented.For this response, a positive group delay means that the pulse is shifted back in time as it passes through an antenna; whereas a negative group delay means it is shifted forward in time.The latter case doesn't necessarily violate causality, it just means that the antenna predicts where the pulse will be in the future, based on where it is now.The negative group delay (NGO) response is highly interested recently for RF and microwave devices including antennas [26].Here, significant NGD values with -14.71, -3.2 and -1.507 ns are found in 2.4, 3.04 and 5.55 GHz.Using a suitable script to interface between AWR and MATLAB simulators, the used parameters in the simulated channel model have illustrated in Table 2.It has been essential here to reference that the entire bit error rate results in this paper are done with some transmitted bits of 10 6 bits and carrier frequency of fc = 2.4 GHz related to the first band of employed antenna.
The channel code is employed for information encoding, and the encoded data has split into different data streams, all of them transmitted, based on numerous transmit antennas.The inward signal at every receive antenna is linear.Figure 6 illustrates BER responses with respect to signal to noise ratio (S/N) for 2PSK digital modulation in the case of Rayleigh channel.It explains as N and M are increased, the BER remains on declining and presents superior BER output as a result of spatial diversity.It has been important to indicate that (SIMO) antenna groupings (1x2 and 1x4) have higher quality BER results unlike (2x1 and 4x1) multiple input single output (MISO) antenna arrangements.This has been due to the received data from an active link makes antenna diversity order of 4 and 8, in which diversity order has been generally twofold a number of receiving antennas.For the number of symbols = 1000000 (transmitted), we can merely measure BER down to 10 −5 consistently as in Figure 6.The most advantageous BER has been found in (4x4) antenna configurations.

Figure 4 .
Figure 4. Phase responses of MIMO antenna Figure 5. Group delay response of MIMO antenna

Figure 6 .
Figure 6.Bit error rate results of 2 PSK MIMO System with several antenna arrangements where the facets in  1 and  2 are calculated as a result of equivalent constituents of   and   .Namely, the kth column vector in the lth row block of the matrix  1 (or  2 ),  = [1  2 ⋯  ]  and  = [1  2 ⋯  ]  .After this representation rule,  ̃ can be defined as: Performance analysis of negative group delay network using MIMO technique (Yaqeen S.Mezaal)

Table 1 .
Dimensions of the proposed MIMO antenna

Table 2 .
The Simulated channel model parameters