Dynamic Spectrum Access Decisions. George F. Elmasry

Dynamic Spectrum Access Decisions - George F. Elmasry


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steps towards grasping the many facets of spectrum sensing through covering the foundations of many of the known techniques to help the system designer select the most appropriate sensing technique for a given system.

Schematic illustration of sensing a wide band of spectrum.

Schematic illustration of the two-dimensional spectrum sensing. Schematic illustration of the three-dimensional spectrum sensing.

      Notice that more dimensions can be added to this multidimensional spectrum sensing technique. For example, the spreading code can be sensed and made a fourth dimension. Spreading code sensing can show opportunistic transmission based on using specific spreading codes. Spectrum sensing of spreading code is covered in Section 2.3.3 as a signal characteristic.

      This is the most common spectrum sensing approach used today. As explained in Chapter 3, the receiver's operator characteristic (ROC) function makes good use of this simple energy detection approach. Chapter 3 covers how same‐channel in‐band sensing can use energy detection sensing with minimal requirements on the receiver to hypothesize the presence of interference.

      A simple receiver can collect the energy received on the antenna in a certain frequency band and quantize it. Low computational complexity and simple implementation are what makes energy detection commonly used. In Figure 2.3, energy detection below a certain power threshold constitutes an opportunity for a spectrum band use (e.g., by a secondary user4). On the other hand, energy detection above that threshold constitutes an occupied band. In Figure 2.3, energy detection is the power axis. Deciding the value of that cutoff threshold can be challenging as the primary user signal may suffer from interference, multipath fading, and jamming among other factors that can affect the signal strength. Energy detection becomes especially more challenging when sensing spread spectrum signals that tend to have low energy. Chapter 3 is dedicated to DSA decision making and will discuss how cutoff thresholds can be used.

      2.3.1 Energy Detection Sensing of a Communications Signal (Same‐channel in‐band Sensing)

      Let us start from the unit of energy of a communications signal Φj(t), which can be defined as follows: If the receiver detects a 1 V signal across a 1 Ω resistor, the integration of the square value of signal voltage over a specific time period (Tg, Tf) is 1, that is, the receiver has detected one unit of energy.5 Notice the following:

      1 The signal can be constructed in a multidimensional signal‐in‐space (SiS) as a vector.6

      2 The time T = Tf − Tg is a critical factor in detecting the signal energy.7 If the signal is too weak, the integration of the square value of the signal voltage may need a long period of time to yield reliable energy detection.

      The receiver of a communications signal detects a multicoefficient signal in N‐dimensional SiS and attempts to match the received signal with one of M signals.8 The energy detector cares only for the signal energy not the signal decoding.

      The signal's ith dimension projected on the kth base can be expressed as follows:

      where Φk(t) is the signal basis per coefficient.

      Notice


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