Название: Dynamic Spectrum Access Decisions
Автор: George F. Elmasry
Издательство: John Wiley & Sons Limited
Жанр: Отраслевые издания
isbn: 9781119573791
isbn:
4 Consider the relationship between SIR and link connectivity discussed in Section 6.2.2. Let us assume the simplest connectivity use case where we have no other cells using the same frequency in the area and there is a single active end user. If the end user desired data rate is 20 Mbps and the selected threshold in Equation (6.2) is Γ = 2, the technique was able to establish a connection for that end user. Will the technique be able to establish the connection if the end user's desired data rate was less? What if the end user's data rate was more?
5 Beam width plays a major role in 5G DSM. Let us assume the general case for the relationship between SIR and link connectivity discussed in Section 5.2 and assume that when all users use a beam of 10° width, the global interference power is 0.1 of the signal power and that global interference power doubles for every 10° increase in beam width.Create a table showing a column for the beam angles incrementing from 10° to 50° in 10° incremental steps. Populate this table with a second column for power ratio as the beam width increases.Add a column to the table showing the SIR in dB.If link closure can only be achieved if SIR in dB > 0, show which entry in the table will cause the node pair to fail in creating connectivity.
6 Consider Figure 6.14 where an end‐user device is given four different options for connectivity through four different access points as shown in the table below. The end‐user device has a desired QoS for the traffic it is using and each access point option has a different QoS guarantee, as shown in the final column in the table.Access pointRateEnergy emissionQoS1R1E1Guaranteed for all rate R12R2 > R1E2 > E1Guaranteed for rate Rx < R13R3 > R2E3 > E2No QoS guarantees4R4 > R3E4 > E3No QoS guaranteesFrom the table, which access point should be eliminated from consideration as the first step?If the end‐user device required data rate is Rr < R1, which access point should be considered?If the end‐user device requires the transmission of a total data rate Rr > R1, but only a fraction of this data rate lower than R1 requires the QoS guarantees, which access point should be considered?
7 A centralized spectrum arbitrator has a pool of eight orthogonal resource blocks and is allocating spectrum resources to four different simultaneous transmit/receive pairs. The algorithm output created the allocation of resource blocks per transmit/receive pair is shown in the table below, where 1 means the block is assigned to the pair and 0 means the block is not assigned to the pair. The spectrum arbitrator is attempting to generate the global energy efficiency metric EEG based on this allocation using Equation (6.12). The EEG calculation assumes that:the power disseminated from an activate resource block (assigned 1 in the table below) is p andthe power received at a block that is not assigned to the transmitter in any given transmit/receive pair is 0.143p where 0.143p is due to orthogonality leakage and other interferences.Block 1Block 2Block 3Block 4Block 5Block 6Block 7Block 8User 110100000User 201010000User 300001010User 400000101Calculate the EEG metric for this assignment in terms of p.If the power received at a block that is not assigned to a transmitter in a transmit/receive pair is 0.333p, calculate EEG metric.What is the impact of increased interference power on the EEG metric?For the same system and the same number of users, let us assume that users 1 and 2 make a request for a high transmission rate while users 3 and 4 make a request for a low transmission rate. Can you redo the table above with different resource blocks assignments?Based on the new table created in (d), if you assume that each resource black can be assigned a transmission rate of r bps, how much rate increase do users 1 and 2 get and how much rate decrease do users 3 and 4 get?Based on 5G requirements for fairness between users, what is the minimum number of resource blocks you would assign to a given transmit/receive pair that makes a request for the lowest data rate?If the spectrum arbitrator recalculates the geographical separation of the four transmit/receive pairs and decides that users 1 and 2 are geographically separated from users 3 and 4 such that resource blocks can be reused, rework the table above with resource blocks reuse assignment based on geographical separation that maximizes the data rate for all four users.If the spectrum arbitrator calculation of geographical separation was not perfectly accurate and the assignment of the same block to two transmit/receive pairs caused the power received at a block that is not assigned to a transmitter in a given transmit/receive pair to increase from a fraction of p as in (a) and (b) above to become p, calculate the EEG metric.Considering the three EEG metric calculations in (a), (b), and (h), what conditions result in the worst EEG metric and what conditions result in the best EEG metric?How important is the role of the sensing function in the end‐user device and how important it is to find a way to update a centralized spectrum arbitrator with the actual measurements of SIR?If you are designing the centralized spectrum arbitrator cognitive engine, what would you want this engine to do if it receives SIR from end‐user devices and finds the EEG metric is approaching the value you calculated in (h)?
8 Section 6.2.3.1 explained the optimization of 5G transmission capacity while relying on the spatial separation metric that uses SIR. Using the formats of the DSA cloud services metrics covered in Chapter 5, draft the details of this spatial separation metric.
Bibliography
1 3GPP standards. WWW.3GPP.org.
2 5G Network Transformation, 5G America. http://www.5gamericas.org/files/3815/1310/3919/5G_Network_Transformation_Final.pdf.
3 Andrews, J.G., Ganti, R.K., Haenggi, M. et al., A primer on spatial modeling and analysis in wireless networks. IEEE Communications Magazine, vol. 48, no. 11, pp. 156–163, November 2010.
4 Andrews, J.G., Buzzi, S., Choi, W. et al., What will 5G be? IEEE Journal on Selected Areas of Communications, vol. 32, no. 6, pp. 1065–1082, June 2014.
5 Aquilina, P., Cirik, A.C., and Ratnarajah, T., Weighted sum rate maximization in full‐duplex multi‐user multi‐cell MIMO networks. IEEE Transactions on Communications, vol. 65, no. 4, pp. 1590–1608, April 2017.
6 Axell, E., Leus, G., and Larsson, E.G., Spectrum sensing for cognitive radio: State‐of‐the‐art and recent advances. IEEE Signal Processing Magazine, vol. 29, no. 3, pp. 101–116, May 2012.
7 Belikaidis, I., Georgakopoulos, A., Demestichas, P. et al. Multi‐RAT dynamic spectrum access for 5G heterogeneous networks: The speed‐5G approach. IEEE Wireless Communications, vol. 24, no. 5, pp. 14–22, October 2017.
8 Chen, S. and Zhao, J., The requirements, challenges, and technologies for 5G of terrestrial mobile telecommunication. IEEE Communications Magazine, vol. 52, no. 5, pp. 36–43, May 2014.
9 Du, B., Pan, C., Zhang, W., and Chen, M., Distributed energy‐efficient power optimization for CoMP systems with max‐min fairness. IEEE Communications Letters, vol. 18, no. 6, pp. 999–1002, June 2014.
10 Elmasry, G., McClatchy, D., Heinrich, R., and Delaney, K., A software defined networking framework for future airborne connectivity. 2017 Integrated Communications, Navigation and Surveillance Conference (ICNS), Herndon, VA, 2017, pp. 1–19.
11 Haider, F. and Gao, X., Cellular architecture and key technologies for 5G wireless communication networks. IEEE Communications Magazine, vol. 52, no. 2, pp. 122–130, May 2014.
12 He, СКАЧАТЬ