4G Cells MIMO CDMA And SDMA Computer Science Essay

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The fourth generation of the mobile communications will be launched in or after 2015. It will come after many years of research (actual start was in 2006) to present many enhanced and developed services.

Many challenges have been raised with the 4G, researchers and companies are struggling to provide wireless coverage for large number of new subscribers, and present new sophisticated services like mobile TV, broadband internet, and video conferencing. These challenging characteristics of 4G require higher capacity channels and more robust links between the base station and the mobile users [1, 2].

The confusing questions are still there with mysterious answers so far; what are the new technologies that will be implemented in 4G? Which technologies of 3G are becoming an old hat, and which are nominated for 4G? Is 4G capable to provide up to 20Mbps downloading rate?

Chapter One: Aims and objectives

1.1 Aims:

The ultimate aims of the 4G are to provide a higher channels capacity, which can be achieved by coupling a MIMO system with a SDMA technique that is based on Adaptive antennas technology. This coupling provides a directed adaptive antenna beam towards the mobile user, with robust wide channel.

As the antenna beam is directed one user is assigned one beam, and since users are spatially distributed beams will not overlap or cross each other, this enables the system to mitigate co-channel interference and channelize users using SDMA to increase the frequency re-use factor.

Adaptive antennas (smart antennas) have techniques so that the beam can track the mobile user as it moves in the base station range (assigned cell), the beam adaptability enhances the system performance in many ways like expand the cell range and enable frequency re-use, so that the system capacity is increased to register new users as efficient spectrum usage is employed. What is more, equipments, installation, and maintenance costs are lowered as the base station coverage area (cell size) is expanded.

In some cases the base station cannot assign one beam for one mobile user, this can happen in one or more of the following reasons (keyhole phenomenon) [18]:

Environment: has scattering, reflecting...etc objects.

Geographic situation: users might be too close to each other or situated on the axis of the beam.

Therefore one beam is assigned for more than one mobile user; this issue hinder the system from communicating properly due to the correlation that is in one beam, for this CDMA in one beam is employed to distinguish between the-one-beam users.

1.2 Objectives:

Design a systems consists of one base station and a large number of mobile users.

Implement MIMO and space time multiple access technique (SDMA) using smart antennas to obtain enhanced beams ( which have smart tracking features) that enable a high channel capacity, spectrum efficiency, as well as robustness (due to receiver diversity).

Apply CDMA in one beam for a group of users to defeat the keyhole issue.

Model the system using Matlab, obtain results, generate a feedback, and then modify the model again to obtain the required aims.

This proposal is a combination of technologies that were employed independently in 3G and older generations, but in 4G the challenge is stronger than before and there is a critical need to use those three technologies together to take an advantage of each in order to contribute in the proposed generation. Previous generations used multiple access schemes in a hybrid way; for instance TDMA and FH. In my proposal I will use MIMO, SDMA, and CDMA. My approach is simply how to operate these techniques to work in one frame in the same time to achieve low cost, acceptance for more users, and provide innovative services.

Chapter Two: Beamforming and Smart Antennas

2.1 Introduction:

The beamforming is forming a single output array from many antenna elements which are overlapped together.

The launch of the concept of the beamforming and smart antennas was first in the 1960s; this was a necessity in order to obtain high SNR by attenuating the noise signal to the possible extent [3].

2.2 Smart Antennas and noise:

Noise, caused by Fading and interference of other users, affects the performance of wireless communication systems and limits the channel bandwidth. This noise can be decreased by using some antenna technique at the base station; this is called beamforming or spatial filtering which combine antenna outputs into one directed output towards the user of interest, the main benefit of that is to reduce the multipath fading and attenuate interference of co-channel users [3, 4, and 7].

2.3 Array pattern:

This term refers to the plot of the array (antenna) response with respect to angle.

In other words this pattern is the value of the antenna power spatial distribution.

Figure 2.3.1 shows a power pattern of a linear antenna (array) of ten elements separated by half of a wavelength. The angle is measured with respect to the line of the array, in this case it can be stated that the beam is directed to a specific user that has an angle of 90o with the line of array. As the angle of a user with the array line decreases or increases (the user is moving) the power value (response) decreases, that means the user of the angle 90o has the maximum power whereas other users have neglected signal strength; that what the term directivity means [5].

Figure 2.3.1: Power pattern of a 10-element linear array with ½λ spacing.

In contrast, figure 2.3.2 shows the main and side lobe of a directional antenna in polar plot, it is easier when the pattern is visualized in this way. The plot shows that this particular antenna has a high power received / transmitted in towards a user of a zero angle with the antenna line; this is referred to as the main lobe [7].

Figure 2.3.2: Polar plot of an antenna pattern

2.4 Architecture:

The adaptive antenna essentially is a set of antennas (sensors), and an adaptive signal processor the gives these elements (sensors) different values to form different beams.

Figure 2.4.1 shows a basic block diagram of an adaptive antenna system. In this diagram it is clear that for a certain user there is one beam formed in a particular direction depending on obtained parameters and information. The adaptive processor requires information like modulation type, signalling format, number of signal paths received at the base station, direction and angle of arrival, the delay of each path, and the complexity of the propagation environment. This information is the input of the processor, so that the output is simply the weight of each element, in result by assigning a specific weight to the array elements, we obtain a beam with desired pattern that is towards the user of interest.

Figure 2.4.1: Block diagram of a basic adaptive antenna

In order to form a desired beam the adaptive processor requires certain algorithms such as MUSIC, ESPRIT, and WSF. Furthermore, other techniques are employed, those use reference or training signals to find the optimum adaptive beamform [4].

2.5 Received power at the antenna:

If we have a system consists of a base station and a subscriber, the received power is given by the following formula (in dB):

, where:


From the previous two equations it can be concluded that by increasing the tolerable path loss we can increase the distance (d) which is the range of the base station. Therefore, employing the smart antennas increases the range and decreases the transmitted power; this yields a less interference between cells. It is noticed that implementing such a technique is more feasible when applied only to the base station rather than the mobile (portable) subscriber terminal [6].

2.6 Digital Beamforming array Antennas (DBF):

DBF technology depends on the DSP advancement. Compared to switched-beam antenna and phased array antennas, DBF has smoother power pattern, and higher resolution direction finding with great speed DSP and very good resolution ADC.

DBF block diagram array antenna is shown in figure 2.6.1. Signal is received by the array elements (Array element1, Array element2 …Array elementn), then down-converted, passed to a low noise amplifier and frequency converter, and to ADC. Signals are converted into digital form in order to be processed in the DSP that employs some algorithm. A fine steering is achievable by employing the high-resolution sampling and quantization in an A/D conversion process [8].

Figure 2.6.1: Functional block diagram of DBF array antennas

2.7 Enhancements achieved by Smart Antenna Technology:

Large range coverage:

Smart antennas provide better coverage due to the focusing on the main lobe.

Reduce initial installation cost:

Smart antennas that can modify the range and the number of users served easily and feasibly, rather than installing new equipment like how it is in the conventional networks if it is necessary

Attenuate multipath fading

Enhanced security

Higher capacity:

Smart antennas enable frequency reuse and reduce co-channel interference [7].

Chapter Three: Code Division Multiple Access (CDMA)

3.1 Introduction:

In this technique the message signal (narrow bandwidth) is multiplied with a spreading signal (large bandwidth). The spreading signal is a pseudo-noise code sequence (PN) which has a chip rate greater than the data rate of the message signal [10]. An interesting fact in CDMA is that all users use the same frequency and time domains (unlike FDMA or TDMA). Each user has a unique pseudo-random codeword that is approximately orthogonal to all other code words, so as a result the user is able to pick up the desired signal, while all other codewords appear as noise signals.

The RAKE receivers are an important part of the CDMA system to give a receive diversity.

This is achieved with aid of power control technique in CDMA [9].

3.2 The concept of spreading:

Spread spectrum means two key facts:

Widen the message bandwidth more than what is needed for the data rate.

Reducing the power spectral density (PSD) of the useful signal the thing that might make it bellow noise signal level.

In figure 3.2.1, Ts is the length of a transmit pulse, N is the number of chips that Ts is divided to (more precisely spreading factor of the signature pulse), and then the length of one chip is:

Note: Simply, the PN is random sequence of '1's and '0's; this sequence is generated by shift registers, what is more, PN is periodic with a period Np.

For instance: PN = α1, α2, α3, α4, α5... where αn {0, 1} [21].

Figure 3.2.1: Signature pulse with N=8 rectangular chips

Here the spreading sequence is given as (+ − + + − + − −) for instance.

Thus increasing the signal frequency from to results in widening the bandwidth N times, figure 3.2.2.

Figure 3.2.2: Power spectral density (PSD) for DS-CDMA

What is more, in CDMA we define the effective spreading factor by:

Where: and [10].

3.3 RAKE receiver:

The spreading might be considered a waste of the bandwidth, but it benefits in enhancing the robustness against the multiple access interference (MAI).

In CDMA we are interested in the main path as well as different multipaths, which enable the multipath diversity. In base station signals are received by RAKE receiver which combines multipaths together.

RAKE consists of certain RAKE fingers (correlators) correlating the received signal to the used code signal. Simply, the RAKE receives multipath signals and determines the delays of propagation, subsequently the correlators use these delay values to adjust the exact timing for the multipath signals, and then as a result those signals can be combined in a maximum ratio combiner [10].

3.4 CDMA and digital beamforming together:

To use CDMA the beamforming techniques must meet some conditions, otherwise implementation is not applicable for the following reasons.

First, all users in a CDMA wireless system are co-channel and their number may easily exceed the number of antennas. Moreover, the receiver receives the main path as well as multipath resulted from reflections and diffractions in the cell, therefore the array might not be defined properly and the goal of the adaptive beamforming might be defeated.

Also, due to the fact that there is no training or reference signals from the mobile user towards the base station, reference-signal based techniques cannot be used too.

Therefore I propose a new space-time processing framework for adaptive beamforming with antenna arrays in CDMA. This approach may be seen as a signal-structure based technique since it exploits both temporal and spatial structure of the received signal [4].

Chapter Four: Multiple-Input Multiple-Output Systems (MIMO)

4.1 Introduction:

The key principle of MIMO is to use multiple antennas for both transmission and reception. Employing this technique increases the wireless channel capacity and enhances the robustness of the wireless link [12].

4.2 MIMO and Diversity:

Diversity has many types and sophisticated techniques such like spatial, frequency, and temporal diversity. Moreover, MIMO enable another kind which is receive and transmit antenna diversity. In receive/transmit antenna diversity; the receiver/transmitter that has multiple antennas receives/transmits multiple replicas of the same transmitted/received signal.

Therefore, when one of the signal paths between each antenna pair fades, the other signal paths are unlikely to suffer a deep fade; this gives stronger robustness to the system and prevents signal outage or decrease [12].

It should not be ignored that receive diversity in cell phones becomes costly and cumbersome to deploy. This is one of the main reasons that transmit diversity became popular at base stations since it is easier to implement there [11].

4.3 Transmit/Receive diversity:

In this case there are controlled redundancies at the base station, which are exploited by a sophisticated signal processing technique at the mobile user.

This requires a full channel information at the base station to make the procedure capable, but this problem were solved by the space-time coding schemes like Alamouti's scheme. In other words the transmit diversity can be implemented without knowledge of the channel the reason that enabled MIMO systems to start being developed rabidly [11].

4.4 Space-time signal model:

Assuming that M is the antenna elements number that used at the base station, n(t) is the added noise ,and Q is the number of users, the received continuous time M-1 signal vector is written as follows:

: is the signal received from the user q [13].

Whereas the matrix form is as follows [14, 16, and 17]:

MIMO technology is used in different ways depending on the number of the transmitter elements and receiver element whether it equals one or greater than one, according to the previous we can define the following four systems:

MIMO: Multiple-input, multiple-output: and

SIMO: Single-input, multiple-output: and

MISO: Multiple-input, single-output: and

SISO: Single-input, single-output: and [15].

In my approach those systems are not used apart from MIMO due to its strength, ease, and efficiency.

4.5 MIMO channel capacity:

Shannon capacity of MIMO channel equals the maximum data rate that can be transmitted over this channel with some error probability.

Capacity versus outage defines the maximum rate that can be transmitted over the channel with some nonzero outage probability.

The channel gain matrix is so important to present information about the channel.

For instance, in case of static channel the capacity is given as follows:


M =min(Nt,Nr)

B: is the bandwidth

is the average SNR per receive antenna under unity channel gain [16].

The previous formula shows how important the turn MIMO system is playing in enhancing the channel capacity.

The MIMO system provides more robustness and higher SNR to the channel; therefore it is used widely and is going to be implemented in the next communications generation 4G as this generation requires a high data rate and an extraordinary fidelity. Employing MIMO systems is certain and a must in future networks which promise to provide exceptional services.

4.6 Space Division Multiple Access (SDMA):

SDMA uses direction as another dimension in signal space, which can be formed as a channel and allocated to different mobile users, which generally done with directional antennas.

The range of the adaptive antenna (2°) is divided into N sectors, as mentioned earlier; a high gain is achieved in the beam direction whereas low interference exists between sectors.

Multiple access schemes are applied within the sector, for instance TDMA or FDMA is used to channelize users within a sector.

For mobile users (the case of my proposal) SDMA must adapt as user angles change, and when the user is about to go out of the current sector, a soft hand over is performed to the adjacent sector or cell [22].


In sum, there is no perfect technology in communications world so far that can be relied on completely and efficiently. However a new innovative model can be implemented by using different techniques in a hybrid scheme, this methodology enables to take the advantages of each technology, and then contribute in the required approach to achieve the desired objectives.