Wireless Communications

Power control (PC)

Objectives:

• Combat the near-far problem (reduce interference due to non-orthogonality of transmissions, increase connection-carrying capacity)
• Reduce transmitted power levels

Classification of PC

• Per reference signal for control
  • Received signal power based PC
  • Received signal-to-interference ratio (SIR) based PC
    • The required average SIR (equal to the target SIR threshold) depends on the Doppler rate (mobile speed), the multipath profile (Power delay profile), the path loss and shadowing.   The required average SNR is w.r.t. a target BER/FER.   Note that the received SNR is a stochastic process (assuming stationary).   The required average SNR is used to set the threshold.
• Per control signal frequency
  • Slow PC: slow enough so that the interval of control actions is larger than the coherence time of small-scale fading; fast enough so that the power control can combat (hopefully, eliminate) path loss and shadowing.
  • Fast PC: fast enough so that the interval of control actions is much smaller than the coherence time of small-scale fading.   Effective for low mobility of mobile terminals; not effective for high mobility of mobile terminals.
• Per control loop structure
  • Outer loop PC (slow PC): set the threshold of SINR for inner loop PC.
  • Inner loop PC (fast PC)
    • Initially, the system uses open-loop PC, i.e., the threshold of SINR is set a priori based on history.
• Per nature of control step size
  • Fixed-step PC
  • Adaptive-step PC (predictive)

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

• Interference-limited system: the interference is dominant in SINR calculation while the noise is negligible (e.g., CDMA system).
• Bandwidth-limited system: the bandwidth is limited (due to FCC spectrum allocation) (e.g., any narrow band system).  These systems are also power-constrained.   Need a modulation scheme with high spectral efficiency.
• Power-limited system: the power is limited (due to FCC specification) while bandwidth may be very large (e.g., ultra wide band system).  Spectral efficiency may be low.