LITMIR.BIZ

       pk, n is the transmit power of the kth transmit/receive pair over the resource block n.

       αk, n, φk, n, and ωk, j, n are positive parameters that depend on the desired systems parameters and propagation model.

       The summation in the denominator is to consider orthogonal signal impact where ωk, j, n depends on the impact of the other users' channels on the resource block n.

       αk, n represents the impact of the kth pair on the signal dimension of the nth block, φk, n.

      1 Power control has to lead to energy emission optimization in different scenarios, including when spectrum assignment decisions are made through a centralized arbitrator (i.e., the macrocell acting as main fusion center, as in Section 6.4.1) and when spectrum assignment decisions are made autonomously by cell access points, as in Section 6.4.2.

      2 When spectrum assignment decisions are made by a centralized arbitrator, the 5G DSM technique should optimize energy emission globally. A metric for global energy efficiency, EEG, can be used to gauge the efficiency of the decisions reached.

      3 The optimization techniques used can be heuristic and may not render the best optimum way all the time. The DSM technique has to consider the tradeoff between accuracy, computational power, and speed of making decisions using heuristic algorithms. Techniques such as fractional programming and heuristic attempts to create sequential convex optimization in large‐scale dense deployments can become challenging.22

      4 When spectrum assignment decisions are made autonomously by a cell access point, the end‐user device can act in a noncooperative manner (consider the case in Figure 6.14). The end‐user device can be aiming to maximize its own energy efficiency and obtain a certain rate of transmission at the lowest power consumption regardless of the impact of its own arbitration decision on the global optimization of energy emission.

      5 Resource blocks are employed for transmit/receive pairs dynamically and are continually assigned and freed, meaning the optimization problem is always trying to reach equilibrium.

      6 There is a tradeoff between global performance in the centralized case and fairness. In an equilibrium problem settings, fairness has to be less subjective and be about not starving one end user of spectrum resources on the expense of another end user.

       pc. k is the power dissipated by the transmitter for the kth transmit/receive pair.

       PK is the power allocation vector over the utilized N resource blocks, which is one of many possible vectors that can be allocated as denoted by in the equation:(6.7)

       The end‐user device has local power constraints , which is the maximum power the device can dissipate. Thus:(6.8)

       In order to create fairness as explained above, we must assure that the end‐user device will have a minimum transmission rate. However, this minimum transmission rate can be illusive if we want to also limit the minimum number of spectrum resources blocks we can assign to an end user. This will require creating a metric that measures the maximum rate that can be achieved for the minimum number of spectrum resource blocks. The term SIRk, nrepresents the maximum SIR we can expect when interference and noise are minimal.

       The end‐user device can be assigned a target data transmission rate in order to achieve fairness. We have to consider that target data rate in terms of SIRk, n. This means the nominator in Equation (6.6) has some boundary data rate. The data rate the end‐user device can achieve, θk, is bounded as:(6.9)