Power control (PC)
Objectives:
Classification of PC
The reference value (e.g., SINR target) for control is adaptive according to network load (intra-cell/inter-call interference), and transmission data rates. A problem is how to determine an (optimal) SINR target such that average transmitted power is minimized, subject to BER<= threshold. What is the optimal control such that the variance of the received signal is minimized?
The Near-Far Problem
CDMA has not been previously implemented due to its "Near-Far Problem." Let's assume there are two users, one near the base and one far from the base.
The propagation path loss difference between these extreme users may be many tens of dB. In general, the strongest received mobile signal will capture the demodulator at the base station. In CDMA, stronger received signal levels raise the noise floor at the base station demodulators for the weaker signals, thereby decreasing the probability that weaker signals will be received.
To help eliminate the "Near-Far Problem", CDMA uses power control. The base station rapidly samples the radio signal strength indicator levels of each mobile and then sends a power change command over the forward radio link. This sampling is done 800 times per second and can be adjusted in 84 steps of 1 dB. The purpose of this is so that the received powers from all users are roughly equal. This solves the problem of a nearby subscriber overpowering the base station receiver and drowning out the signals of far away subscribers. An extra benefit is extended battery life. That is, when a mobile unit is close to a base station, its power output is lower. In other words, the mobile unit transmits only at the power necessary to maintain connection.
In wireless communication, spectral efficiency is typically 1 bit/s/Hz; for example, use BPSK and root raised cosine pulse.
Why do we need a wireless network in cellular structure? Because a base station cannot cover the whole target area, we need to partition the area into cells, each of which has a base station.
Why do we need mobility management? Because if we don't know which cell the called party is, how can we make a call? Hence we need mobility management to track users so that they can be called (once you know the location of the called party, you know how to set up a path between the caller and the called).
Mobility pattern
Christian Bettstetter. Smooth is Better than Sharp: A Random Mobility Model for Simulation of Wireless Networks. In Proc. 4th ACM International Workshop on Modeling, Analysis, and Simulation of Wireless and Mobile Systems (MSWiM), Rome, Italy, July 2001.
There are several factors affecting the communication performance (e.g., throughput, SNR, BER). However, there may be only one dominant factor that limits the performance. For example, we have the following systems
Orthogonal Frequency Division Multiplexing (OFDM),
which is a multi-carrier modulation scheme, is a strong candidate for future
communication systems to achieve high data rates in multipath fading
environments. In OFDM, the wide transmission spectrum is divided into
narrower bands and data is transmitted in parallel on these narrow bands.
Therefore, symbol period is increased by the number of sub-carriers, decreasing
the effect of inter-symbol interference (ISI). Adaptive modulation is a
method to increase the throughput of wireless communication systems. In adaptive
modulation, the transmitter continually monitors the time-varying fading channel
and adjusts the transmission parameters accordingly to maximize efficiency.
Adaptive modulation consists of three components: channel estimation, modulation
selection and signaling/blind classification of the modulation used.
Signaling of the modulation used consumes bandwidth but with high reliability
for demodulation; blind classification of the modulation used saves bandwidth
but at high computation cost at the receiver. Blind
classification uses pattern recognition techniques or detection techniques such
as maximum likelihood detector and Bayesian detector.
Hybrid automatic repeat request (hybrid-ARQ) schemes combine ARQ protocols with forward error correction codes (FEC) to provide increased throughput in packet transmissions. HARQ schemes may be classified as Type-I, Type-II and Type-III Hybrid ARQ schemes depending on the level of complexity employed in there implementation.
• Type I Hybrid ARQ: retransmit the whole channel coding packet (no
combining)
On a decoding error, this ARQ scheme discards erroneous packets and sends a retransmission request to the transmitter. The entire packet is retransmitted on receipt of the NACK. The packets are combined based on either the weighted SNR.s of individual bits or soft energy values, in which case the technique is termed Chase combining (see the reference as below).
D. Chase, .Code combining . A maximum likelihood
decoding approach for combining an arbitrary number of noisy packets,
IEEE Trans. Commun., vol. 33, pp. 385 . 393, May 1985.
• Type II Hybrid ARQ: retransmit a packet containing parity-check bits;
combine the previous packets to form a larger codeword. (progressive
combining)
In this ARQ scheme, retransmission requests consist only of parity bits. The receiver combines additional parity bits from retransmission with bits of the first transmission resulting in lower rates, before FEC decoding is attempted.
• Type III Hybrid ARQ: selective combining of received packets.
In Type III ARQ schemes, individually transmitted packets are self-decodable and each packet differs in coded bits from the previous transmission. In Type III ARQ, packets are only combined after decoding has been attempted on the individual packet. Use selective combining. For example, three packets can have seven kinds of decoding, i.e., 3 single packets, 3 combinations of two packets, 1 combination of three packets.
Handoff
SOFT HANDOFF in cellular code-division
multiple-access (CDMA) systems is a technique whereby mobiles near cell
boundaries communicate the same transmitted signals to more than one base
station (BS) within their vicinity. Soft handoff is important because it
provides enhanced communication quality and a smoother transition compared to
the conventional hard handoff. On the reverse-link, signals transmitted by
mobiles in the handoff area may reach all the nearby BS¡¯s, even though the
signals are not intended for them and the mobile signals appear as interference
in these nearby cells. By putting more matched filters in the receiver, BS¡¯s can
receive signals from mobiles in the nearby soft-handoff areas. Notice that no
extra channels are required to accomplish soft handoffs on the reverse links.
Soft handoff provides macrodiversity, which is due to more than one BS being
involved in the communications. The signal-to-interference ratio (SIR) is
improved by combining the signals from the different BS¡¯s, and this, in turn,
increases reverse-link quality and extends cell coverage. As there are at least
two BS¡¯s involved in the soft-handoff process, where each BS supports a
forward-link channel to the mobile, the number of available channels on the
forward link decreases as the number of mobiles in soft handoff increases. We
investigate this effect on the system capacity.
Sectorization in cellular CDMA systems increases the capacity in proportion to
the number of sectors per cell. For a sectorized CDMA system, there are two
kinds of handoff when mobiles move from one sector to another, namely, handoff
between two sectors in different cells and between two sectors within a cell.
Similar to soft handoff, softer handoff is the soft handoff between two sectors
of the same cell. For a perfect sectorized antenna pattern, softer handoff
cannot be applied. In practice, the antenna patterns do not fit the sector area
perfectly, and there is an overlapping of the two antenna patterns between the
sectors. The overlapping of the sector antenna patterns generates additional
interference on both the reverse and forward links.