Wireless vs. Wireline

Wireless technology is playing a profound role in networking and communications, even though wireline technologies such as fiber have inherent capacity advantages. Relative to wireless networks, wireline networks have had greater capacity and historically have delivered faster throughput rates.

While wireless networks can provide a largely equivalent broadband experience for many applications, for ones that are extremely data intensive, wireline connections will remain a better choice for the foreseeable future. For example, users streaming Netflix movies in high definition consume about 5 Mbps. Typical LTE deployments use 10 MHz radio channels on the downlink and have a spectral efficiency of 1.4 bps/Hertz (Hz), providing LTE an average sector capacity of 14 Mbps. Thus, just three Netflix viewers could exceed sector capacity. In the United States, there are approximately 1,100 subscribers, on average, per cell site8, hence about 360 for each of the three sectors commonly deployed in a cell site. 

In dense urban deployments, the number of subscribers can be significantly higher. Therefore, just a small percentage of subscribers can overwhelm network capacity. For Blu-ray video quality that operates at around 16 Mbps or Netflix 4K streaming that runs at 15.6 Mbps, an LTE cell sector could support only one user.

Even if mobile users are not streaming full-length movies in high definition, video is finding its way into many applications, including education, social networking, video conferencing, business collaboration, field service, and telemedicine.

Over time, wireless networks will gain substantial additional capacity through  the methods discussed in the next section, but they will never catch up to wireline. One can understand this from a relatively simplistic physics analysis:

q  Wireline access to the premises or to nearby nodes uses fiber-optic cable.

q  Capacity is based on available bandwidth of electromagnetic radiation. The infra- red frequencies used in fiber-optic communications have far greater bandwidth than radio.

q  The result is that just one fiber-optic strand has greater bandwidth than the entire usable radio spectrum to 100 GHz, as illustrated in Figure 1.

Figure 1: RF Capacity vs. Fiber-Optic Cable Capacity

A dilemma of mobile broadband is that it can provide a broadband experience similar to wireline, but it cannot do so for all subscribers in a coverage area at the same time. Hence, operators must carefully manage capacity, demand, policies, pricing plans, and user expectations. Similarly, application developers must become more conscious of the inherent constraints of wireless networks.

Mobile broadband networks are best thought of as providing access to higher-capacity wireline networks. The key to improving per-subscriber performance and bandwidth is reducing the size of cells and minimizing the radio path to the wireline network, thus improving signal quality and decreasing the number of people active in each cell. These are the motivations for Wi-Fi offload and small-cell architectures.

Optimization phase | Network Planning

Once the planning and implementation are complete, it is very common practice to run drive tests for the planned sites. Drive tests verify the predictions made by the planning tools, and the results from the drive tests are compared against the results from the simulations. Fine tuning is performed after the drive tests to ensure that the deviation in the results between simulation and drive tests is minimal.

A part of the drive test, parameters like reference signal receive power (RSRP), reference signal received quality (RSRQ), or SINR the UL and DL throughputs at different points of the cell are noted. The results are then compared with the SNR predictions made by the planning tool and deviations are noted and tuned wherever required.

Coverage Planning

Coverage planning targets for the complete service area are tested to ensure there are no coverage holes (i.e., the UE never experiences a no-service condition within the entire service area). Coverage plans, however, do not take into consideration any quality of service that the user experiences within a cell or site. The end aim is to provide the count of the resources or eNodeBs and cells that are required for the complete service area.

Some of the most important aspects that need to be considered as a part of the coverage planning are:

1.       The eNodeB transmitting power and the type of cell that is being planned. The eNodeB transmitting power is the key for any coverage planning, and the transmitting power will vary based on the cell size. For example, a macro cell will have a transmission power of 10 watts per port (40 watts per cell in cases of MIMO cells). The DL coverage cell radius should be derived based on the transmission power of the antenna added with the gains (antenna gain, diversity gain, etc.) with the assumption of path loss (receiver loss, propagation loss, etc.). Cell radius calculation will be covered in detail in the link budget calculation section.

2.       The eNodeB receiver sensitivity. In the uplink, in order to calculate the cell radius, one of the most important parameters that the operator relies on is the receiver sensitivity of the eNodeB. The eNodeB receiver sensitivity is a deciding factor for the maximum allowed path loss between the UE and the eNodeB in the uplink direction, beyond which the eNodeB cannot differentiate accurately between signal and noise. Better receiver sensitivity of the eNodeB will directly result in a larger cell radius (coverage radius) in the uplink. The 3GPP 36.141 defines the test for deriving the reference sensitivity of a receiver.

The specification also requires that a receiver sensitivity of less than -100.8 decibel milliwatts (dbm) is acceptable. However, many vendors have a receiver sensitivity value of around -102 dbm or better.

3.       UE receiver sensitivity and transmission power. Similar to the eNodeB receiver sensitivity, UE receiver sensitivity is an important factor in determining the DL cell radius for coverage planning. Typically for a macro cell, the UL cell radius will be a limiting factor in comparison with the DL cell radius simply because of the difference in the transmission powers. In LTE category 2 UE and onward, the maximum uplink transmit power is 23 db.

4.       Terrain. Terrain is an important consideration for any site planning and will impact the absorption or attenuation capability of a site. For example, a site with irregular heights will not have linear loss and is subjected to shadow areas or reflection, whereas a site with fairly regular height will have a more predictable linear loss. Similarly, the indoor to outdoor ratio of a site also makes a difference when it comes to cell radius calculation (i.e., the penetration losses for an indoor user is higher compared with that for an outdoor user); therefore, planning an urban cell will be subject to more losses due to a higher percentage of indoor to outdoor users in comparison with a rural cell.

Unsolicited Grant Service with Activity Detection

The UGS-AD algorithm is designed to support real-time service flows that generate fixed-size data packets on a semi-periodic basis (e.g., VoIP using on–off voice codec). It incorporates activity detection, which makes it suitable for use with on/off voice codecs. The algorithm uses combined features of UGS and rtPS. UGS-AD has two scheduling modes: UGS and rtPS, and can switch between these modes depending on the status of the voice users (on or off). On initialization of VoIP services, this algorithm starts with the rtPS mode. While in rtPS mode, if the voice user requests bandwidth size of zero bytes, the BS maintains this (rtPS) mode. However if the user requests bandwidth size greater than zero, the BS switches its mode to UGS. While in UGS mode, if the voice user requests bandwidth size = 0, the BS switches to rtPS, and if the user requestsbandwidth greater than zero, the BS stays in UGS. By switching between rtPS and UGS modes, the UGS-AD algorithm significantly addresses the problem of UL resources wastage in the UGS algorithm, and the MAC over head and access delay in the rtPS. This is however only for the case where the voice user uses voice codecs with only two data rates (on–off). Where voice codecs with variable data rates like EVRC is used, resources wastage still occur in the UGS-AD algorithm. In this case, the wastage occurs during the on duration, when full resources is assigned eventhough the variable data rate of voice codecs means that it will not operate at full rate for all of the time the resources is allocated. The operation of the UGS-AD algorithm is illustrated in Figure 1.

 
Figure 1: UL resource allocation using UGS-AD algorithm.