Research Article
a
November
2018
Computer Science and Software Engineering
ISSN: 2277-128X (Volume-8, Issue-11)
Directivity Analysis for Massive MIMO Beamforming for
Next Generation Wireless Communication Systems
Irfan Nissar Bhat, Harish Kumar Dogra, Sehba Yousuf
Department of ECE, SSCET Badhani Punjab, India
[email protected], [email protected], [email protected]
Abstract— The paper is deliberated towards the study of the Radio Direction finding technique for incoming Radio signals. These radio signals could be friendly or from a hostile source, primarily finding its use for Military as part of Electronic Warfare and other civil application. There are various techniques which are in vogue; they have their advantages and limitations. The conventional technique i.e. Beamscan, for direction finding is studied and beam forming is explained. This technique has inherent limitations of giving inaccurate results under certain conditions, therefore better technique known as Minimum Variance Distortionless Response (MVDR) is used for closely impinging waves. No single technique suffices the requirement of Radio Direction of Arrival estimation for Electronic Support Measures of EW. It is intended that the new methodology devised will optimize the Estimation of Direction of arrival, under all conditions regardless of the technique used with least of Human Operator's intervention. In this paper we present the effect of the transmit diversity on the quality of signal reception at the receivers side. The technique involves the computation of the directivity at the receivers for different input parameters like Beamscan angles, polarization and tapering techniques like Chebyshev, hamming etc. The results finally reveal that Massive MIMO employed with Beamforming leads to considerable amount of capacity enhancement at the receiver.
Keywords— (BeamformingTechniques, MVDR, Transmit Diversity, Massive MIMO, Radiation Pattern)
I. INTRODUCTION
Beamforming is a technique of delivering high power beam towards wanted client while creating nulls towards interferers.It is like wise alluded to as directional transmission or reception of a signal.Present period is the fourth era of versatile systems.It is assumed that the imminent fifth era of cellular communications will give a data rate of 10 Gbps.This high information rate can be refined by different systems.Anyway to getsuch a high information signaling rate,there is apre requisite of high frequency wave.Massive mimo beamforming can be utilized to accomplish such a high information rate with high frequency wave to be carried with mm wave arrays. Comprehensively beamforming systems can be classified into conventional beamforming and adaptive beamforming .In conventional beamforming antenna array has fixed set of patterns which can be utilizedwhile transmission and reception of signals.However that is not not the situation with adaptive beamforming which progressively change the array design according to the receivers.Inconventional beamforming we are very much aware about the Channel state Information(CSI) of a communication link while that is not the situation with adaptive beamforming[3].SO amiddle road procedure is tobe utilized with the end goal to accomplish the two objectives ie CSI as well as well as dynamic array design.That strategy is alluded to as hybrid beamforming. .An example of radiation pattern in case of beamforming is shown in fig-1.
Fig-1. Example of a radiation pattern
ISSN(E): 2277-128X, ISSN(P): 2277-6451, pp. 21-27
executed is through full duplex systems utilizing different number of antennas[2].But, it experience a genuine disadvantage of strong self interference from its transmit antennas. This strong self interference can be obliterated impressively by the consolidated use of baseband analog cancellation and RF domain approach, in any case if multiple antenna beamforming is fused in the framework the whole leftover self interference can be prohibited along these lines making full duplex systems entirely interference free. Beamforming has been favoured over different methods in view of its property of high gain and interference alleviation. For future wireless communication systems design and execution of smart antennas likewise alluded to as adaptive reception apparatus arrays increased much consideration. These effficient reception antennas when utilized can upgrade the limit and in addition scope of the framework using adaptive beamformers which deliver nulls towards interferers and direct the primary beam towards the coveted user[1]. This significantly expands the signal interference proportion. In contemporary remote systems an enhancement of antenna gain and intereference mitigation is for the most part accomplished through beamforming strategies. Convent ional beamforming essentially utilized for analog systems required high consumption on the equipment, anyway digital beamforming can be executed through programming accordingly taking out the cost required for equipment setup. Beam designs if there should arise an occurrence of digital beamformers are controlled utilizing distinctive calculations, for example, MI (Matrix Inversion) for fixed beamforming and LMS (Least Mean Squares) , RLS (Recursive Least Squares) calculations for adaptive beamforming. Digital beamforming can be sorted into two kinds based on entry edge at the gathering. At the point when the arrival angle does not change with time array weights require not to be changed to drive the array components for acquiring beam design.This is alluded to as fixed beam forming.However when the arrival angle changes with time the weights of array should be changed progressively to get different beam designs according to need .This is alluded to as adaptive beamforming[4].
II. RELATED WORK
Adnan Anwar et.al [1] in 2017 took a shot at the structure and usage of smart antennas utilizing diverse beamforming techniques .Different algorithms were utilized by the sort of beamforming procedure actualized and the execution correlation was made based on nulls area, gain and Half Power Beam Width(HPBW). After re-enactment it was presumed that the gain of MI algorithms diminished definitely when the interferers were conveyed nearer to principle client. Anyway LMS calculation likewise confronted a similar pattern for gain yet it demonstrated somewhat proficient as far as HPBW. In the event of RLS algorithms the gain additionally debased as the separation between SNOI (Signal Not of Interest) and SOI (Signal of Interest) were conveyed near one another however HPBW remained genuinely consistent therefore giving prevalent execution relatively .MI calculation was consolidated for fixed beamforming while as LMS and RLS were actualized for adaptive beamforming.Duckdong Hwang et.al [2] in October 2017 proposed in his paper about the plan of a powerful device for upgrading throughput and spectral efficiency utilizing full duplex frameworks which can bolster countless devices. Anyway full duplex systems encounter solid self-interference. In this paper he formulated a procedure of smothering this self-interference by presenting the joint methodologies of RF domain and baseband analog suppression to limit interference impacts up to bigger degree. Anyway the execution of beamforming techniques stifled whole leftover interference present in full duplex systems subsequently making them nearly interference free. In this paper he additionally figured a procedure of collecting energy from interference for charging the batteries at the recipient end as opposed to smothering it through the procedure of self-energy recycling.M.shoriful Islam et.al [3] in 2016 proposed some beamforming techniques for the upcoming fifth era of cell communications. In this paper he looked at performance investigation of various beamforming techniques like conventional adaptive and hybrid beamforming to understand the most productive beamforming method .He utilized diverse neural system models to acknowledge adaptive beamforming. Right off the bat hop field model was utilized to break down MMSE beamforming ,also he utilized feed forward system to discover input output relationship .From reproduction and results he demonstrated that the hybrid beamforming is most proficient and practical over digital and analog beamforming.Rothna et.al [4] in 2015 proposed two receive beamforming techniques to remunerate the Carrier Frequency Offset [CFO] in the receivers .In this paper a performance correlation of various beamforming techniques in presence of CFOs was analysed. Conventional beamforming when executed does not yield CFO compensation, anyway when joint receive beamforming and spatial selectivity receive beamforming was actualized and it was observed that spatial selectivity receive beamforming was more robust in presence of CFO errors contrasted with corrupted performance of joint receive beamforming techniques.
III. SYSTEM MODEL
ISSN(E): 2277-128X, ISSN(P): 2277-6451, pp. 21-27
antenna and not an individual antenna itself. In the nonexclusive sense, the execution of any antenna array increments with the quantity of elements, yet the disadvantages for a substantial number of elements is the expanded expense and size. The arrangement of these antennas can be in any mold (i.e. line, framework, and so on.). It is at first expected that all array elements are indistinguishable. Be that as it may, the excitation (both amplitude and phase) connected to every individual element may contrast. The far field radiation from the array in a direct medium can be processed by the superposition of the EM fields produced by the array elements. Consider an antenna array with N elements, where the input signals are represented as X1, X2, X3, X4, and so on till Xn. Let the individual element weight be w1, w2, w3, w4…wn
as shown in the following figure.
Figure-2. Received Signal And Element Weights
Antenna elements, usually have (x, y) = (0, 0) and only the Z axis value changes and there of the distance lambda/2. This means that the elements are half wave separated.
Figure-3. Parallel wave fronts of the infinite signal
The electric field of these half wave separated antenna elements where it is initially assumed that the wave received has uniform amplitude everywhere.
Where „k‟ represents the wave vector, which the variation of phase as a function of position.
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If the radiation pattern of each antenna element is given by (𝜃,∅). Y can be written as follows,
where 𝑟 = [𝑥, 𝑦, 𝑧] of the antenna elements. The above equation can be modified as
Where, the AF is called as the Array Factor. The array factor is a component of the antenna element weights and their positions. It is an essential capacity, as the adjustment in weights on this capacity, will enable it to alter the course of most extreme transmission or gathering in like manner.Here the w, weights allude to the values, which partition the aggregate input current going to every receiving antenna element by some particular proportion. This particular proportion of current division can be picked dependent on the measure of required side projection level concealment. More about the weights proportion will be talked about, when the array is energized with non-uniform amplitude excitation.
Array Factor particularised: A more profound knowledge into the Array factor is given as pursues. The field of an isotropic radiator situated at the starting point might be composed as
A supposition here is that elements are consistently separated with a separation
Figure-4. Far field of the array with constant element spacing
In the far field,(𝑟1 = 𝑟 ) ,( 𝑟2 ≈ 𝑟 – 𝑑cos𝜃) ,(𝑟3 ≈ 𝑟 − 2𝑑cos𝜃) , ( 𝑟𝑁≈ 𝑟 − (𝑁 − 1) cos𝜃)
The current sizes, the array elements are thought to be equivalent and the current on the array element situated at the inception is utilized as the phase reference (zero phase).
𝐼1 = 𝐼𝑜𝐼2 = 𝐼𝑜𝑒𝑗∅2𝐼3 = 𝐼𝑜𝑒𝑗∅3 … 𝐼𝑁= 𝐼𝑜𝑒𝑗∅𝑁
The overall array far field is found using superposition as is given as
𝐸𝜃 = 𝐸𝜃1 + 𝐸𝜃2 + 𝐸𝜃3 + ⋯ + 𝐸𝜃𝑁
𝐸𝜃= [1 + (∅2+2𝑘𝑑cos𝜃) + (∅3+2𝑘𝑑cos𝜃) + ⋯+ (∅𝑁+ (𝑁−1) 𝑘𝑑cos𝜃)]
𝐸𝜃= 𝐸𝑜[𝐴𝐹]
Where, Array Factor 𝐴𝐹 = [1 + (∅2+2𝑘𝑑cos𝜃) + (∅3+2𝑘𝑑cos𝜃) + ⋯ + (∅𝑁+ (𝑁−1) 𝑘𝑑cos𝜃)]
Let us now consider, a uniform N linear antenna array, where the spacing between elements is uniform, uniform amplitude and a linear phase progression.
∅1 = 0 ∅2 = 𝛼∅3 = 2𝛼 …. ∅𝑁= (𝑁 − 1)
Inserting this linear phase progression into the formula for the general N- element array gives
𝐴𝐹 = [1 + (∅2+2𝑘𝑑cos𝜃)+ (∅3+2𝑘𝑑cos𝜃)+ ⋯+ (∅𝑁+ (𝑁−1) 𝑘𝑑cos𝜃)]
= 1 + 𝑒𝑗Ψ+𝑒𝑗2Ψ + ⋯ + (𝑁−1) Ψ
(Ψ = 𝛼 + 𝑘𝑑𝑐𝑜𝑠𝜃) =∑N
n=1 ej (n-1) Ѱ
The capacity is characterized as the array phase function and is a function of the element spacing, elevation angle. On the off chance that the array factor is multiplied by , the outcome is
ISSN(E): 2277-128X, ISSN(P): 2277-6451, pp. 21-27
AF (ejѰ-1) = (ejNѰ-1) AF =ej (N-1) Ѱ/2
Here complex exponential term represents the phase shift of the array phase centre relative to the origin. If the position of the array is shifted in order to locate the centre of array towards origin this phase term goes away. The array factor can be written as
Some general characteristics of the array factor AF with respect to Ψ: [AF] max = N at Ψ = 0 (main lobe).
Total number of lobes = N-1 (one main lobe, N-2 side lobes). Main lobe width = 4 π/N, minor lobe width = 2 π/N
The array factor may be normalized so that the maximum value for any value of N is unity.
When the denominator is not zero, the nulls of an array factor can be determined from zeros of numerator.
𝑛 ≠ 0, 𝑁, 2𝑁, 3N,
When the denominator is not zero, the peaks of an array factor can be determined from zeros of numerator.
IV. RESULTS AND SIMULATION
Figure -5 (part 1) and Figure -5 (part 2) evaluates the qualitative analysis of the beamforming with different number of sensor elements. Without beamforming we find that the radiation pattern is uniformly distributed over the entire geographical area. This leads to the loss of power in non-intended areas and hence needs to be preserved. With the application of the beamforming at the transmitter side we are able to direct the radiation pattern in a particular direction and always directs in the direction of the intended user. The 2D plot with azimuth cut in line depicts the two dimensional directivity pattern as a function of the azimuth angles. The 2D plot with azimuth cut polar depicts the same pattern in polar coordinates. The 3D radiation pattern depicts the three dimensional view of the radiation pattern for clear understanding. We also evaluated the effect of the transmit diversity on the beamforming and find that Massive MIMO in conjunction with beamforming enhances the signal reception quality at the receiver side. We also made a quantitative analytical comparison of the different array characteristics and the directivity obtained.
ISSN(E): 2277-128X, ISSN(P): 2277-6451, pp. 21-27
Figure-5. 2D pattern with azimuth cut-line, 2D pattern with azimuth cut-polar and 3D polar plots for different number of Sensor elements. (Part2)
V. CONCLUSIONS
The technique involves the computation of the directivity at the receivers for different input parameters like Beamscan angles, polarization and tapering techniques like Chebyshev, hamming etc. The results finally reveal that Massive MIMO employed with Beamforming leads to considerable amount of capacity enhancement at the receiver.We also evaluated the effect of the transmit diversity on the beamforming and find that Massive MIMO in conjunction with beamforming enhances the signal reception quality at the receiver side. We also made a quantitative analytical comparison of the different array characteristics and the directivity obtained.
ACKNOWLEDGMENT
Special thanks to the department of Electronics and Communication Engineering Sri Sai college of Engineering and Technology Badhani in supporting this research work.
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