Beamforming and Generating Beam Patterns

The cell layout used for the purpose of this research consists of 7 eNodeBs (single tier network) as depicted in Figure 3-8, with an ISD of 500 m. The simulation is performed by defining a RoI (target sector) in which the eNodeBs and UEs are positioned and it is only in this area where UE movement is performed. Each sector has 10 UEs, and the performance metric of the UEs in sector 13 (target sector) are taken in to account. This is because the sector is in the middle of the layout, and receives interference from all surrounding eNodeB sites, therefore avoiding optimistic results at the cell-edge. It has to be taken into account that the figures (Figure 3-10 to Figure 3-12) illustrated throughout the section have a lower resolution for illustration purposes.

Received power to each of the geographical position in each sector from its respective eNodeB is calculated depending on the distance, path-loss and shadow fading from the eNodeB and logged in a matrix. This matrix was generated to support the TS36.942 [136] antenna model.

To determine the geographical areas with bad channel conditions, the calculated received power (power received by an UE from the relevant eNodeB) values at each point are used. The received power is calculated using the Equation 3-7 and logged in a matrix:

( )

( )

64 For the transmitting antenna, G the radiation power density at a distance r from the antenna is W. Here, the arguments θ and ɸ indicate a dependence on direction from the antenna, and Pt stands for the power the transmitter would deliver into a matched load (receiver).

This matrix which includes the received power value for each position depending on the distance from the eNodeB can be used to generate receiver beam patterns using different power levels at the eNodeB to investigate the coverage, or to determine the power needed to cover a certain area (e.g. cover the UEs in the range of < 120dB) as shown in Figure 3-10 (lower resolution has been used for illustration purposes).

These patterns are generated using the fixed beam antennas covering the geographical positions which are inside the given received power range. It can be observed that most of the radiation power is fallow and it extends beyond the cell-edge boundary, causing interference at the next cell sector.

As an example, Figure 3-11describes the fixed beam pattern generated using a 4 x 4 antenna which covers the geographical positions inside the receiver power range of < 80dB.

Figure 3-12 illustrates how the average coverage and interference changes when the number of UEs is increased, in order to check the consistency of the simulator. In total 50 iterations were performed and the results were averaged for the fixed beam radiation pattern. Users are generated randomly and a range of 10 up to a maximum of 25 UEs inside a sector was considered. The ‘x’ denotes a geographical position and a ‘o’ represents a UE. Using the antenna receiver radiation power at each geographical position the simulator can change the antenna radiation pattern to cover a specific area as shown in the figure. From Figure 3-12 can be observed that in average 85% of the UEs are covered by the generated fixed beam patterns (CoMP not required).

-800 -600 -400 -200 0 200 400 600 800 -600 -400 -200 0 200 400 600

66

To perform coordinated multipoint, beamforming techniques were taken into consideration based on which new antenna receiver beam patterns are generated, for specified UE locations (positions) in each sector. It was assumed that the direction (angle) and the UEs’ distance to are known to the eNodeB (eNodeB is aware how UEs are distributed across the network). In addition, the Direction of arrival (DoA) from all randomly generated UEs is calculated and the average angle is taken in to consideration when the eNodeB generate the gain pattern.

There are several methods discussed in the LTE Rel. 9 [86] standard that can be used to acquire the position of UE. From these techniques the Enhanced Cell ID (E-CID) method [86] provides several benefits since it calculates the angle and the distance to an UE, by using timing measurements (based on round trip time) to calculate how far a mobile terminal for example is from the eNodeB [17, 74]. When connected, both the serving cell and the UE measure the timing difference between Rx sub-frames and Tx sub-frames. The UE reports the

5 10 15 20 25 10 20 30 40 50 60 70 80 90 Number of UEs % users covered interfered users users not covered

measured values to the eNodeB and the eNodeB calculates the round trip time (RTT) required for determining the position.

Since the eNodeB’s coordinates and antenna height are also known the position of the UE can be calculated. This method can be further improved with the addition of a feature known as Angle of Arrival (AoA). There are several methods such as ESPRIT and MUSIC [143, 144] discussed in literature for the calculation of AoA. The eNodeB estimates the direction from which the UE is transmitting using a linear array of equally spaced antenna elements. Reference signals received from the UE at any two adjacent elements are phase rotated by an amount which depends on the AoA.

By increasing the number of antenna elements in the eNodeB the generated beam pattern can be narrowed to a specific UE or an area only. Therefore a smart antenna system needs to differentiate the desired signal from co-channel interference and normally requires either the knowledge of a reference signal (or training signal), or the direction of the desired signal source which can be calculated using any of the above methods mentioned above [145].

Even though the direction and angle of arrival were calculated by taking the average of all angles to all UEs from an eNodeB, the receiver beam pattern generated with a fixed antenna configuration is not able to cover all positions in a sector in the absence of CoMP techniques. Since the simulator has the knowledge of the received power value of each geographical position, the antenna radiation pattern to be used for each sector in 3 – sector cell site is plotted using the matrix generated by using Equation 3-1.

Figure 3-13 shows how each antenna radiation pattern covers the geographical positions

which are within their given received power (dB) range. Since the received power value at each geographical position is known, it can be used as a reference point for developing power control algorithms at eNodeBs and UEs, to combat cases of high power consumption.

68 Combining algorithms for reducing radiation power at specific directions with receiver beamforming techniques, as will be described in following sections, can minimise interference. Currently Figure 3-13displays the fixed antenna beam patterns of a single tiered network in the absence of any beamforming techniques used and with fixed beam antenna (SISO) configuration.

In use of fixed antennas the interference due to constant radiation power which is made worse by beam overlap is significantly higher compared to an adaptive smart antenna scenario. Therefore to overcome this problem the receiver beamforming technique using smart antennas is introduced. Receiver beamforming will be demonstrated and evaluated in detail in chapter 4, for transmission in the uplink of a cellular network in order to focus energy at a

specific UE or cluster of UEs providing in cooperation with other techniques interference mitigation.