Copyright 2018 Thomas Schwengler.

Chapter 2
Cellular Systems

Wireless communications are especially useful for mobile applications, so wireless systems are often designed to cover large areas by splitting them into many smaller cells. This cellular approach introduces many difficulties such as how to avoid interference, or how to hand-over from one cell to another, while maintaining good service quality. Coverage, capacity, interference, and spectrum reuse are important concerns of cellular systems; this chapter reviews these aspects as well as the technologies, tools, and standards used to optimize them.

2.1 Cellular Concepts

Providing wireless service over wide areas requires different schemes to efficiently use spectrum in different locations while avoiding interference.

2.1.1 Frequency Reuse

Covering a large geographic area with limited amount of spectrum leads to the reuse of the same frequency in multiple locations; this leads to co-channel interference considerations, meaning interference from different areas (or cells) that use the same frequency channel.

Co-channel interference considerations are usually approached by considering the following parameters:

The three quantities are linked by the straightforward relation:

St = S0K

The reuse factor K is therefore an important parameter for capacity. The lowest reuse factor (K = 1) maximizes capacity; but this has to be balanced with interference considerations: indeed a higher reuse factor (K = 3, 4, 7, or higher) provides more distance between cells using the same frequency, which lowers interferences.

2.1.2 Interference and Reuse

Spectrum reuse causes interference; quantifying them require us to consider how a signal propagates from one cell to another. We will study propagation models later in chapter 3, but we need a few simple notions here. Assume a propagation model using a power path loss exponent n, that is a model where power decays in 1∕Rn (R being the distance separating transmit station from receiver). This means that the ratio of received power to transmit power may be expressed as Pr∕Pt = A∕Rn, where A is some constant.


Figure 2.1: Frequency reuse patterns K =3, 4, and 7, on hexagonal cells. Bold contour shows the pattern of cells repeated to provide wide area coverage. Di shows the shortest distance between cells reusing the same frequency.

With this model, signal to interference ratios are estimated as

        R -n
S∕I = --i0----n-
      Σ i=1D i

where i0 is the number of co-channel cells nearest to the cell (called first tier or tier one); that number increases with K. And Di is the distance to the tier-one cells reusing the same frequency (as shown in figure 2.1). In the case of hexagonal cell approximation the expression simplifies to [1]:

       √ --- n
S∕I =  (-3K-)--

We’ll see more details on n further, its values vary typically between 2 and 4 with the types of terrain. We’ll also see that specific wireless technologies require a certain signal to noise and interference ratio (mostly based on data rates); so equation (2.3) leads to a minimal acceptable value for K.

2.1.3 Multiple Access

A major requirement of cellular networks is to provide an efficient technique for multiple devices to access the wireless system. These techniques include:

frequency division multiple access, perhaps the most straightforward, in which every user device uses its own frequency channel. This method was used in the first generation analog systems.
time division multiple access, in which a radio channel is divided in time slots, and use devices use their allocated time slots. In fact TDMA systems are often hybrid FDMA as well as multiple channels are used, most 2G systems were TDMA.
code division multiple access, in which orthogonal (or pseudo orthogonal) codes are used to differentiate user devices. CDMA is very spectrum efficient, and was used by 3G standards. There are several approaches to achieve CDMA, such as frequency hooping (FH-CDMA)or direct spreading (DS-CDMA).

These are the main multiple access techniques, but subtle extensions and combinations can be devised to obtain more efficient schemes, which we will examine in later chapters (including orthogonal frequency division multiplexing - OFDMA).

2.2 System Capacity

Wireless communications deal with at least two main concerns: coverage and capacity. We will look at coverage prediction in the next chapters, and start here with a few words on capacity.

2.2.1 Channel Capacity

One fundamental concept of information theory is one of channel capacity, or how much information can be transmitted in a communication channel. In the 1940’s Claude Shannon invented formal characterization of information theory and derived the well-known Shanon’s capacity theorem (Theorem 17 in [15], p.628). That theorem applies to wireless communications. A great presentation of this equation can be found in [8] p.82; it presents a concise derivation of the equation, and includes a good introduction to important information theory concepts such as information and entropy. 1

The Shannon capacity equation gives an upper bound for the capacity in a non-faded channel with added white Gaussian noise:

C =  W log2(1+ S∕N )

where C= capacity (bits/s), W=bandwidth (Hz), S∕N= signal to noise (and interference) ratio.

That capacity equation assumes one transmitter and one receiver, though multiple antennas can be used in diversity scheme on the receiving side. The formula will be revisited for multi-antenna systems in 9.1.3. The equation singles out two fundamentally important aspects: bandwidth and SNR. Bandwidth reflects how much spectrum a wireless system uses, and explains why the spectrum considerations seen in 1.2 are so important: they have a direct impact on system capacity. SNR of course reflects the quality of the propagation channel, and will be dealt with in numerous ways: modulation, coding, error correction, and important design choices such as cell sizes and reuse patterns.

2.2.2 Cellular Capacity

Practical capacity of many wireless systems are far from the Shannon’s limit (although recent standards are coming close to it); and practical capacity is heavily dependent on implementation and standard choices.

Digital standards deal in their own way with how to deploy and optimize capacity. Most systems are limited by channel width, time slots, and voice coding characteristics. CDMA systems are interference limited, and have tradeoffs between capacity, coverage, and other performance metrics (such as dropped call rates or voice quality).

Cellular analog capacity:
Fairly straight forward, every voice channel uses a 30 kHz frequency channel, these frequencies may be reused according to a reuse pattern, the system is FDMA. The overall capacity simply comes from the total amount of spectrum, the channel width and the reuse pattern.
TDMA/FDMA capacity:
In digital FDMA systems, capacity improvements mainly come from the voice coding and elaborate schemes (such as frequency hopping) to decrease reuse factor. The frequency reuse factor hides a lot of complexity; its value depends greatly on the signal to interference levels acceptable to a given cellular system ([1] ch. 3.2, and 9.7). TDMA systems combine multiple time slots per channels.
CDMA capacity:
a usual capacity equation for CDMA systems may be fairly easily derived as follows (for the reverse link): first examine a base station with N mobiles, its noise and interference power spectral density dues to all mobiles in that same cell is ISC = (N - 1), where S is the received power density for each mobile, and α is the voice activity factor. Other cell interferences IOC are estimated by a reuse fraction β of the same cell interference level, such that IOC = βISC; (usual values of β are around 12). The total noise and interference at the base is therefore Nt = ISC(1 + β). Next assume the mobile signal power density received at the base station is S = REb∕W. Eliminating ISC, we derive:
        W-- ---1--  1- --1--
N = 1 +  R ⋅Eb ∕Nt ⋅α ⋅1 + β⋅


This simple equation (2.5) gives us a number of voice channels in a CDMA frequency channel 2.

We can already see some hints of CDMA optimization and investigate certain possible improvement for a 3G system. In particular: improving α can be achieved with dim and burst capabilities, β with interference mitigation and antenna downtilt considerations, R with vocoder rate, W with wider band CDMA, Eb∕Nt with better coding and interference mitigation techniques.

Some aspects however are omitted in this equation and are required to quantify other capacity improvements mainly those due to power control, and softer/soft handoff algorithms.

Of course other limitations come into play for wireless systems, such as base station (and mobile) sensitivity, which may be incorporated into similar formulas; and further considerations come into play such as: forward power limitations, channel element blocking, backhaul capacity, mobility, and handoff.

2.3 Modulation and Coding

Modulation techniques are a necessary part of any wireless system, without them, no useful information can be transmitted. Coding techniques are almost as important, and combine two important aspects: first to transmit information efficiently, and second to deal with error correction (to avoid retransmissions).

2.3.1 Modulation

A continuous wave signal (at a carrier frequency fc) in itself encodes and transmits no information. The bits of information are encoded in the variations of that signal (in phase, amplitude, or a combination thereof). These variations cause the occupied spectrum to increase, thus occupying a bandwidth around fc; and the optimal use of that bandwidth is an important part of a wireless system. Various modulation schemes and coding schemes are used to maximize the use of that spectrum for different applications (voice or high speed data), and in various conditions of noise, interference, and RF channel resources in general.

Classic modulation techniques are well covered in several texts [1][8], and we simply recall here a few important aspects of digital modulations (that will be important in link budgets). The main digital modulations used in modern wireless systems are outlined in table 2.1.


Bits encoded by:


Amplitude Shift Keying

Discrete amplitude levels

On/off keying

Frequency Shift Keing

Multiple discrete frequencies

Phase Shift Keying

Multiple discrete phases


Quadrature Ampl. Mod.

Both phase and amplitude

16, 64, 256 QAM

Table 2.1: Digital modulations

Modulation is a powerful and efficient tool used to encode information; a few simple definitions are commonly used:

denotes the physical encoding of information, over a specific symbol time (or period) Ts, during which the system transmits a modulated signal containing digital information.
denotes a logical bit (0 or 1) of information; one or more bits are encoded by a modulation scheme in a symbol.

Higher order modulations can encode multiple bits in a symbol, and require higher SNR to decode error-free. Figure 2.2 illustrates how multiple phases and amplitudes are used to combine multiple bits into one symbol transmission. The tradeoff between bits encoded per symbol is often referred to as a measure in bits per Hertz (b/Hz), its relation to SNR is bounded by Shannon’s theorem seen earlier (2.2.1).


Figure 2.2: Digital modulations encode multiple bits of information over the transmitted signal. The simplest modulation (BPSK) simply encodes one bit of information in the sign of the wave. Higher order modulations combine orthogonal signals (sine and cosine) and multiple amplitudes to encode multiple bits: 2 in QPSK, 4 in 16 QAM, and 6 in 64QAM.

2.3.2 Coding

Efficient coding schemes are the powerful engines behind the growth of the wireless industry. They have allowed wireless systems to be both spectrally efficient and robust in terms of error corrections.

Block coding are the classical approach: blocks of data are used as input to produce usually larger output blocks containing added redundancy.

Second generation wireless systems like cdmaOne introduced the use of convolutional coding. The coding scheme provides an efficient redundant and error-correcting scheme. This is particularly useful for voice transmission where the need for retransmission causes delays and degrades voice quality.


Figure 2.3: Convolutional coding consists in sending a data stream of bits into an encoder that produces multiple output streams.

Wireless data systems of higher rates often use turbo coding, which are a combination of two convolutional coders reading each other (the name comes from the turbo-charged engine, which uses some of its output power to compress some air fed to the intake, and is somewhat reminiscent of the turbo coding diagram of figure 2.4).


Figure 2.4: Turbo coding consists in splitting a data stream, and sending it and an interleaved replica into convolutional encoders.

Convolutional coding and turbo coding are example of continuous coding schemes, where a bit stream is encoded into another bitstream, usually of greater speed (with a multiplier of 2, 3, 4 or more). The added number of bits can be seen as spreading the spectrum, and the information, which requires more data to transmit, but inherently contains useful redundancy properties (a form of time diversity). The decoding of such schemes was historically difficult and has become possible only with recent processing power (see for instance Viterbi algorithms [115]).

2.3.3 Combined Modulation and Coding

The combination of modulation and coding provides great flexibility between redundancy and throughput. Higher modulation increases spectral efficiency in good propagation condition; when conditions worsen, lower modulation helps, but increased redundancy is sometimes an efficient alternative. Combined, the two schemes can reach impressive efficiencies, close to Shannon’s limit (2.2).

2.4 Standard Air Interfaces

We first briefly review current mobile digital technologies, how they were initially introduced, and how and they evolved. 3

First Generation Analog cellular phones:
Advanced mobile phone service (AMPS) was developed by Bell Laboratories in the 1970’s, and started in the US after FCC allocation in 1983 of 40 MHz paired spectrum in the 800 MHz frequency range. The system used a frequency divided modulation access (FDMA), duplex frequencies for up and down link (frequency division duplexing - FDD), with 30 kHz channels, one user per channel, analog voice modulation (FM), blank and burst transmission.

RF channel

30 kHz

Reuse pattern

typically 7



Multiple access



1 traffic channel per RF channel


FM modulation

Second Generation Digital wireless systems:
Second generation cellular systems are characterized by the introduction of voice digitizing and digital encoding, thus opening a number of DSP possibilities such as forward error correction schemes. Frequency or time division multiple access techniques are used (FDMA or TDMA). Code division multiple access (CDMA) is introduced by Qualcomm (TIA-EIA IS-95, or ANSI-95) and becomes the basis for the main 3G systems. Overall capacity is increased, signaling capabilities and system intelligence is considerably enriched.

RF channel

30 kHz, 200 kHz in GSM, 1.25 MHz for CDMA

Reuse pattern

7 (less with frequency hopping), 1 for CDMA


mostly FDD (emergence of TDD)

Multiple access

FDMA, TDMA (8 full-rate time slots for GSM), or CDMA


Digital encoded: GSM full rate 13.4 kbps, CDMA 13 kbps QCELP or 8 kbps EVRC

Third generation systems:
Digital systems were further improved upon, mostly for higher voice capacity and higher data rates; they evolved into third generation standards.

RF channel

1.25, 5, 10, 15 MHz

Reuse pattern

1 (CDMA)


mostly FDD, some TDD

Multiple access



Digital encoded: bit rates 8 kbps and below


Up to several Mbps (3.1 Mbps for EV-DO, 15 Mbps for HSDPA)

Fourth generation systems:
Fourth generation standards deal with higher throughput, low latency, IP network architecture. Air interfaces focus on multicarrier techniques like OFDM, and advanced antenna systems such as multiple input multiple output (MIMO) systems.

RF channel

generally wider: 10, 20 MHz, more

Reuse pattern



FDD or TDD depending on spectrum

Multiple access





IP based, flat architecture, convergence

Fifth generation systems:
Fifth generation definition vary greatly, from software defined radio (SDR) to adaptation to any new radio interface as needed. Today’s 5G focus revolve around improving throughput, lowering latency,and target products to be deployed in the year 2020.

2.5 Speech Coding

The introduction of digital wireless systems means that the acoustic voice wavefront is not simply converted to an electrical signal directly transmitted over RF channel. Voice is now digitized, encoded, and the resulting bit stream is transmitted and of course decoded on the receiving side. Although this process requires additional digital signal processing (DSP), it opens the door to many optimization algorithms and is much more efficient than usual analog voice transmission.

2.5.1 Basic Vocoder Theory

Digital voice coding (vocoding) is very important yet very subjective. Voice coding theory is a domain of study of its own; introductory overviews are presented for instance in [1] ch. 8 or [2] ch. 15.

2.5.2 Classic Cellular Vocoders

Analog vocoders have emerged at Bell Laboratories in the late 1920’s, and have become more elaborate and efficient in dealing with harmonics important to a good understanding of voice (500 Hz to 3400 Hz) while minimizing bandwidth. The digital area brought significant changes. Initial digital systems sampled that range, which at the Nyquist rate leads to a 64 kilobits per second (kbps, kbit/s, or kb/s) bandwidth. This is referred to as pulse-code modulation (PCM). More elaborate algorithms however can achieve reasonably good voice transmission by transmitting a codebook (set of parameters for a given voice coding algorithm) with as little as 2.4 kbps rate: a 26-fold improvement. Usually these algorithms provide acceptable voice quality, but may provide poor performance in specific situations such as in a noisy environment, with background music, or when combined with different voice coding systems (such as PCM or voice mail systems). Several vocoder systems exist and have been chosen in 2G and 3G standards:

Code Excited Linear Prediction, 2.4 and 4.8 kbps, Federal Standard 1016, used in STU-III.
Qualcomm Code Excited Linear Prediction, developed in 1994, was used in initial IS-95 CDMA networks. Two bit rates available: QCELP8 and QCELP13 using 8 and 13 kbps respectively, which is well adapted for this standard’s 9.6 kbps and 14.4 kbps frames. It was later improved upon by EVRC.
Relaxed Code Excited Linear Prediction, a more advanced advanced algorithm that does not attempt to match the original signal exactly but a simplified pitch contour.
Enhanced Variable Rate CODEC is a speech codec used in CDMA networks, it uses RCELP 8 kbps and improves quality over 8QCELP. Half rate EVRC were also developed to further lower bitrate at the cost of some quality.
Continuously Variable Slope Delta-modulation, 16 kbps, used in wide band encryptors such as the KY-57.
Mixed Excitation Linear Prediction, MIL STD 3005, 2.4 kbps.
Adaptive Differential Pulse Code Modulation (G.721, G.726).
Adaptive Multi-Rate, extensively used for GSM with variable rates from 12.2 kbps for enhanced full rate down to 4.75 kbps and even 1.8 kbps. The latest voice coding effort revolve around Voice over LTE (VoLTE), also rely on AMR. Narrowband AMR (AMR-NB) has a 8 kHz sampling rate. Wideband AMR (AMR-WB) has double the sampling rate to cover the 50 to 7000 Hz voice range, and has 9 different codec modes with data rates from 6.6 to 23.85 kbps.

Comparing the quality differences between vocoder is usually done by testing a number of standard phrases, and assessing the quality of the transmitted result under various conditions. That assessment is subjective and is usually given a grade called Mean Opinion Score (MOS) between 0 (completely unintelligible) and 4 (perfect quality). Initial tests relied on actual opinion surveys, but test devices now offer algorithms providing a MOS and are regularly used by wireless network operators to benchmark network quality.

2.6 3G Migration

Second generation cellular systems certainly achieved major capacity improvements and contributed to the fast adoption of wireless handsets throughout the world. And the growth continues.

Third generation systems focused on increasing capacity yet again, and on introducing high-speed mobile data. Given recent heavy investments in different 2G networks, adoption of a common 3G standard had tremendous cost and competitive implications.

Several proposals:
Initially 10 new proposals were submitted to the ITU body responsible for standardizing next generation systems: 2 TDMA, 8 CDMA. (See details in US contribution to the ITU: US8F01-16, February 2001.)
Harmonization process:
A difficult harmonization effort was undertaken from 1998 to 2001 by the ITU. Many technical comparisons and discussions ensued, resulting in some harmonization, but falling short of selecting one unique worldwide standard. TDMA solutions disappeared. CDMA solutions were narrowed down to two. Spectrum plans and emission levels were also agreed upon with some success.
Two CDMA proposals remained: the 3G partnership project (3GPP) proposed UMTS (WCDMA), and 3GPP2 proposed cdma2000. Each side was backed by major wireless carriers. Each side was reluctant to make concessions to the other. 3GPP wanted to maximize a new standard while 3GPP2 added backward compatibility with cdmaOne. Discussions stalled; neither camp had any incentive in giving in, hence two competing standards: UMTS-WCDMA and cdma2000.


Figure 2.5: Multicarrier CDMA2000 is backward compatible with existing cdmaOne channels (left); while UMTS broader spreading (right) is not.

In 2002, CDMA Americas Congress (San Diego, December 2002) estimated that cdmaOne operators benefited from a smooth transition and a well-known standard, thus giving them a one or two year advance over GSM efforts towards UMTS. Indeed cdma2000 (3G 1X) systems have been available since 2002, IS-856 (3G-1X EV-DO) since 2004. GPRS and UMTS caught up around 2006. High-speed data services (HSPA) still lagged in coverage behind EV-DO in 2008.

2.7 4G Migration

According to most definitions (from the ITU in particular), 4G systems focused on increasing air interface efficiency to reach throughput rates around 100Mbps for mobility and 1Gbps for fixed wireless access. Additional requirements (mostly on the network infrastructure) such as low latency, flat IP architecture, small cells, and heterogeneous networks were specified as well.

Oddly enough two different camps emerged again: LTE and WiMAX, each backed up by different suppliers, and different operators, both using very similar technologies (based on OFDMA), yet unable to harmonize to a unique standard.

Long Term Evolution of the current GSM/UMTS/3GPP set of standard is OFDMA on the forward link, and SC-FDMA (a single carrier OFDMA scheme) on reverse link. Interestingly, GSM carriers migrated once to CDMA, and now propose to abandon it for OFDMA. LTE promises to carry much of the international crowd of operators and create economies of scale, allow for international roaming, etc.
WiMAX is a wireless standard based on IEEE 802.16e (and its evolution 802.16m). Its strength is that (unlike other 4G standards) its evolution path preserves backward compatibility with current 802.16e systems.

WiMAX continues to see some success in fixed wireless applications in developing areas. But practically the vast majority of the mobile industry is following LTE (since 2010), making it the de facto 4G standard.

2.8 5G Migration

5G standards are still in the works; an FCC order on 5G spectrum [14] notes no current intent to define what qualifies as 5G, but refers to standard bodies like 3GPP and the ITU. (See 5G news).

Techniques largely revolve around LTE advances and focus on higher throughput, lower latency; they include: flexibility around many spectrum bands (including unlicensed, and millimeter-waves), higher order (even massive) MIMO, considerations for many more devices (Internet of things), direct device to device communications (D2D), and many more features described in releases 14 and beyond of LTE (see 8.3).

2.9 Technology Advances

Recent technology advances aim at increasing capacity further. Technology improvements are sometimes the result of a major standard modification, but sometimes simple schemes that can be added to existing standards and allow for additional improvements with minimal infrastructure changes.

2.9.1 Speech Coding Improvement

Voice coding algorithms and DSP capabilities have improved, and current voice codecs operate on less power, and with greater processing efficiencies. (Refer to [2] ch. 15, or [1] ch. 8 for speech coding details). GSM for instance is improving voice digitization and quantizing from RPE-LPT to a series of Adaptive Multi-Rate (AMR) standards. IS-95 systems have a parallel evolution, with EVRC (at 8 kbps), and half-rate EVRC.

Another standard for selectable mode vocoder (SMV) was in the work but never saw any success in the industry; it based requirements on: operation in presence of frame erasures, noise suppression recommended for background noises, reasonable performance with music for on-hold situations, equivalent performances with different languages, multiple quality modes and multiple bit rates, seamless transition from mode to mode. SMV was design to offer four modes of operations: from mode 0 designed to improve voice quality over EVRC with the same capacity to mode 3 for operators willing to sacrifice some voice quality robustness in order to realize a significant capacity gain. The resulting capacity vs. quality tradeoffs seem useful and attractive to service providers, yet this standard never took off, which may illustrate that some standard evolutions (even when based on sound requirements and good improvements) may miss their window of opportunity.

Voice over LTE (VoLTE), usually relies on wideband AMR with 9 different codec modes with data rates from 6.6 to 23.85 kbps.

2.9.2 Efficient Coding and Modulation

For systems primarily designed for voice, latency was a main concern, and modulations were chosen to be reliable and operating well at fairly low SNR (like QPSK). For data systems it is advantageous to take advantage of higher modulation schemes such as 16QAM and 64QAM when the radio link allows it. Higher modulations are more spectral efficient but prone to more bit error rates and may cause more retransmissions, latency, or jitter.

Data bursts:
when low SNR allows for it, use higher modulation and coding rates for better spectral efficiency.
Adaptive modulation:
fast modulation changes frame by frame allow for efficient scheduling of high speed data bursts when the radio channel is capable of it.
Forward Error Correction:
a very important aspect of wireless communication: error-correcting coding varies from voice to data bursts; block coding, convolutional coding, and turbo coding can be used optimize efficiency.
automatic retransmit requests are used to lower modulation when necessary and retransmit faded data.

2.9.3 Interference Mitigation

Interferences may be cancelled or mitigated by changing antenna patterns as required. Such systems are sometimes referred to as smart antennas; they can steer a main lobe toward a user, or create a null in the direction of an interferer. Some systems are passive others include active amplification devices. The main types of smart antenna systems may be described as follows:

Active antennas:
An array of passive and active elements using multiple power amplifiers on the transmit side, and a low-noise amplifier on the receive side.
Switched beams:
A fixed array of narrow beams, combined to form various size sectors.
Adaptive arrays:
An array of elements offering several degrees of freedom to steer a beam in a certain direction, or create nulls. Array element are sometimes amplified, or attenuated, or are purely passive and utilize phase shift to create the wanted patterns.
Spatial Division Multiple Access (SDMA):
A sophisticated combination of many adaptive elements.

Smart antenna systems are efficient in dense areas but often costly [9]. They are now replaced by MIMO systems covered in chapter 9.

2.9.4 Other Optimization Techniques

Technology advances and standard improvements target an increase in capacity, coverage, data rate, or some other system performance aspect. In many cases however some simple optimization techniques can be used to increase performance:

These techniques are very important tools used by operators to optimize capacity and coverage. In some cases optimization may be seasonal due to foliage or different usage patterns. In all cases RF network demand constant tweaking to provide optimal performance. More recently self optimizing networks (SON) have the ability to continually and automatically optimize these parameters.

2.10 Fixed Wireless Access

Fixed wireless access is sometimes referred to as wireless local loop (WLL), and is an alternative to provide Plain Old Telephone Services (POTS) and high-speed data services in remote areas where wired solutions are impractical for various reasons. In most cases, trenching long distances to place communication conduits (for fiber or copper) is very costly, such as in mountainous areas. Cellular service is often scarce too in remote areas.

2.10.1 Classic Architectures

Radio solutions for wireless local loops were rolled-out extensively since the 1970’s. Early systems used analog radios to offer voice service over fairly long distances. Newer WLL systems need to be cost-effective, reliable, and compliant with local exchange carrier technical, legal, and regulatory standards. But the demand for WLL services are generally low, and suppliers consequently treat the opportunity as a fairly low priority.

Initially WLL focused on providing extensions of the public switched telephone network (PSTN) and its Class 5 features (such as call waiting, caller ID, 3-way calling, and others). Connectivity to Class 5 telephony switches is specified in Telcordia standards such as GR-303 or GR-008; and WLL systems evolved to use these standard interfaces to the PSTN.

Radio frequencies were allocated for wireless local loop applications, and are referred to as Land Mobile Radio (LMR). LMR radio links for telephony use frequencies in the UHF/VHF band (138-512 MHz), which provide great propagation characteristics even in difficult terrain and heavy tree density. These frequencies however are becoming very rare. In fact, they are in such demand that the FCC recently mandated radio systems to increase their spectral efficiencies, and use only a narrow band of spectrum. (See FCC order FCC-04-292, December 23, 2004.)

Other radio solutions work in the 2.4 GHz and 5 GHz unlicensed bands, building on economies of scale of 802.11 radios, with interference concerns - especially when providing emergency service (911 life line).

2.10.2 Fixed Wireless Propagation

Fixed radio links usually behave differently from mobile radio links, they are typically less variable in time (therefore easier to predict and equalize), and their fading statistics are generally easier to deal with. Consequently fixed propagation is usually advantageous for a wireless system and has a significant impact on reach and capacity.

For all the above reasons, fixed wireless links often provide increased reach and capacity than equivalent mobile links.

2.10.3 Voice Integration

The problem remains however to interface these systems with the telephony network. A VoIP gateway can be used to interface with the telephony switching fabric. Telcordia standards GR-008 or GR-303 for instance describe how to connect to a switch (over T1 lines), and access its classic telephony features (such as call waiting, caller ID, 3-way calling, etc.)

Several protocols are available to establish a reliable IP session that can provide voice transport, including session initiation protocol (SIP), or and Media Gateway Control Protocol (MGCP); ITU recommendation H.323 also provides interoperability standards for multimedia communications over IP including voice features. Modern standards generally rely on IP Multimedia Subsystem (IMS) to provide voice services.

2.11 Homework

  1. In a table, list all the wireless technologies popular in modern wireless services (2G, 3G, Wi-Fi, WiMAX, HSPA, LTE). Research and list their main parameters such as: (a) frequency of operation; (b) RF channel bandwidth; (c) peak uplink and downlink data rates; (d) standard body for air interface; (e) modulation type; (f) multiple access; (g) and some kind of capacity estimate such as throughput per MHz.
  2. Examine the Shannon capacity equation and comment on what happens in to channel capacity in the following different situations.
    1. You operate in a fixed bandwidth W0, and increase the power (S) in the channel. How does capacity behave?
    2. You have a limited power radio (therefore S is fixed); you increase system bandwidth, but as you do that system noise typically increases as well: N = N0W (where N0 is a fixed noise density). How does capacity behave as bandwidth increases indefinitely? (calculate limit of C as W →∞).
    3. You now fix the power spectral density: S0 (recall that S = S0W,S0 is your fixed transmit power density). How does capacity increase with bandwidth W?
  3. Calculate the capacity (in voice channel per cell per MHz) of the following standards (see 2.2 and 2.4). In each case, simply assume K = 7 as the reuse factor.
    1. Verify that AMPS system capacity in independent of the amount of spectrum available, and is m = 4.7 ch./cell/MHz.
    2. Calculate GSM full rate system capacity. (Answer: m=5.7)
  4. CDMA capacity improvement:
    1. What capacity gain does a CDMA service provider achieve by changing its handset from QCELP vocoders to EVRC vocoders?
    2. In addition, the better speech coding allows typical Eb∕Nt to be reduced from 7 dB to 6.5 dB. What is the total capacity gain?
  5. CDMA capacity:
    1. Derive in details the capacity formula (2.5) for CDMA systems.
    2. Compute a radio system capacity (mCDMA) for IS-95 half rate EVRC (Eb∕Nt=6.5 dB)
  6. Different radio standards system capacity:
    1. Compare radio system capacity for above IS-95 half rate EVRC, GSM half rate voice frames, DECT, and PHS (search online, or refer for instance to [1] chapter 11 for the last 2).
    2. What are the chances of PHS or DECT to evolve into a 3G standard?
  7. You invented a new voice coder that allows you to code voice in 4.8 kbps rather than 9.6 kbps with no significant voice degradation.
    1. What will the link budget improvement be?
    2. Using capacity equations, quantify network capacity impact.
  8. As an operator, you are faced with the difficult decisions of having to regularly upgrade your network to better standards and newer equipment. Assume you are operating a GSM network and you consider upgrading it to UMTS. Consider (a) price and availability of equipment, (b) timeline to upgrade, (c) impact of other carriers timeline, (d) field experience and proven technology, (e) other considerations.
  9. Similarly to the above problem, you now operate a UMTS network with voice and high-speed packet data. Write a proposal to upgrade it to a fourth generation system using LTE (with the same above considerations).
  10. You operate a wireless service in a small town. You installed a CDMA system that can typically support 50 mobile calls per sector, but you chose to offer fixed service only. Refer to section 2.10, estimate all the gain you can realize and assume that they have a direct impact on the system Eb/No. How would you estimate your fixed system capacity.

Copyright 2018 Thomas Schwengler.