Resource Optimization in Wireless Communications: Fundamentals, Algorithms, and Applications provides an easy-to-understand overview of the fundamentals of resource optimization, along with the latest algorithms and applications for emerging 5G, and beyond, wireless systems offering a variety of services. Additionally, it covers the principles and resource optimization of some systems expected in 6G.
This book is suitable for courses in wireless communications that cover the principles of multicarrier and OFDM, the theory of resource allocation, power allocation, and subcarrier allocation, as well as the principles and optimization of OTFS, ISAC, reflective intelligent surface (RIS)-assisted mmWave, and user-centric cell-free wireless systems. It is also an ideal self-study reference text for researchers and industry engineers who wish to deepen their knowledge while researching and developing wireless systems for 6G.
1. 1.1 Introduction - p. page1 2. 1.2 Multicarrier transmission - p. 2 3. 1.3 Orthogonal frequency-division multiplexing - p. 9 4. 1.4 Filtered OFDM - p. 20 5. 1.5 Modeling of wideband OFDM channels - p. 36 6. 1.6 Summary - p. 42 7. Bibliography - p. 44 8. Chapter 2. General theory and applications of resource optimization in wireless communications - p. 45 9. Chapter 3. Power allocation - p. 77 10. Chapter 4. Subcarrier allocation - p. 105 11. Chapter 5. Beam and channel acquisitions in mmWave systems - p. 143 12. Abstract - p. 143 13. 5.1 Introduction - p. page143 14. 5.2 Hybrid beamforming in mmWave channels - p. page143 15. 5.3 Beamformed MIMO channel model - p. page147 16. 5.4 Beam and channel acquisition in HBF systems - p. 156 17. 5.5 Summary - p. 163 18. Bibliography - p. 163 19. Chapter 6. Beam-based resource allocation in MIMO-OFDM networks - p. 165 20. Abstract - p. 165 21. 6.1 Introduction of MIMO and massive MIMO - p. page165 22. 6.2 Beam selection and allocation in MIMO-OFDM systems - p. 174 23. 6.3 MIMO-OFDM networks with hybrid beamforming - p. 176 24. 6.4 Beam allocations in single-BS HBF MIMO systems - p. 182 25. 6.5 Beam allocation in multi-BS HBF MIMO networks - p. 183 26. 6.6 Beam allocations in CoMP HBF MIMO networks - p. 188 27. 6.7 Summary - p. 200 28. Bibliography - p. 200 29. Chapter 7. Game-theory-assisted resource allocation - p. 201 30. Chapter 8. Machine/deep-learning-based resource allocation - p. 219 31. Chapter 9. Deep-reinforcement-learning-aided resource allocation in ultradense networks - p. 241 32. Chapter 10. Resource allocation in multicell OFDMA systems - p. 259 33. Chapter 11. Distributed resource allocation in multicell MC/DS-CDMA systems - p. 279 34. Chapter 12. Resource allocation for ultrareliable low-latency communications - p. 303 35. Chapter 13. Resource allocation in massive machine-type communications - p. 317 36. Chapter 14. Resource optimization in reflective intelligent surface (RIS)-aided mmWave systems - p. 349 37. Abstract - p. 349 38. 14.1 Introduction - p. page349 39. 14.2 A conceptual example - p. 357 40. 14.3 RIS-mmWave: single-RIS single user - p. page356 41. 14.4 RIS-mmWave: single-RIS multiple users - p. 377 42. 14.5 RIS-mmWave: multiple-RISs multiple users - p. 376 43. 14.6 Concluding remarks - p. 381 44. Bibliography - p. 382 45. Chapter 15. Signaling and optimization in orthogonal time–frequency–space (OTFS) and related schemes - p. 383 46. Chapter 16. Optimization in MIMO integrated sensing and communications (ISAC) - p. 405 47. Chapter 17. Optimization in user-centric cell-free (UCCF) wireless networks - p. 427 48. Bibliography - p. 453 49. Index - p. 471
Resource Optimization in Wireless Communications: Fundamentals, Algorithms, and Applications provides an easy-to-understand overview of the fundamentals of resource optimization, along with the latest algorithms and applications for emerging 5G, and beyond, wireless systems offering a variety of services. Additionally, it covers the principles and resource optimization of some systems expected in 6G.
This book is suitable for courses in wireless communications that cover the principles of multicarrier and OFDM, the theory of resource allocation, power allocation, and subcarrier allocation, as well as the principles and optimization of OTFS, ISAC, reflective intelligent surface (RIS)-assisted mmWave, and user-centric cell-free wireless systems. It is also an ideal self-study reference text for researchers and industry engineers who wish to deepen their knowledge while researching and developing wireless systems for 6G.
1. 1.1 Introduction - p. page1 2. 1.2 Multicarrier transmission - p. 2 3. 1.3 Orthogonal frequency-division multiplexing - p. 9 4. 1.4 Filtered OFDM - p. 20 5. 1.5 Modeling of wideband OFDM channels - p. 36 6. 1.6 Summary - p. 42 7. Bibliography - p. 44 8. Chapter 2. General theory and applications of resource optimization in wireless communications - p. 45 9. Chapter 3. Power allocation - p. 77 10. Chapter 4. Subcarrier allocation - p. 105 11. Chapter 5. Beam and channel acquisitions in mmWave systems - p. 143 12. Abstract - p. 143 13. 5.1 Introduction - p. page143 14. 5.2 Hybrid beamforming in mmWave channels - p. page143 15. 5.3 Beamformed MIMO channel model - p. page147 16. 5.4 Beam and channel acquisition in HBF systems - p. 156 17. 5.5 Summary - p. 163 18. Bibliography - p. 163 19. Chapter 6. Beam-based resource allocation in MIMO-OFDM networks - p. 165 20. Abstract - p. 165 21. 6.1 Introduction of MIMO and massive MIMO - p. page165 22. 6.2 Beam selection and allocation in MIMO-OFDM systems - p. 174 23. 6.3 MIMO-OFDM networks with hybrid beamforming - p. 176 24. 6.4 Beam allocations in single-BS HBF MIMO systems - p. 182 25. 6.5 Beam allocation in multi-BS HBF MIMO networks - p. 183 26. 6.6 Beam allocations in CoMP HBF MIMO networks - p. 188 27. 6.7 Summary - p. 200 28. Bibliography - p. 200 29. Chapter 7. Game-theory-assisted resource allocation - p. 201 30. Chapter 8. Machine/deep-learning-based resource allocation - p. 219 31. Chapter 9. Deep-reinforcement-learning-aided resource allocation in ultradense networks - p. 241 32. Chapter 10. Resource allocation in multicell OFDMA systems - p. 259 33. Chapter 11. Distributed resource allocation in multicell MC/DS-CDMA systems - p. 279 34. Chapter 12. Resource allocation for ultrareliable low-latency communications - p. 303 35. Chapter 13. Resource allocation in massive machine-type communications - p. 317 36. Chapter 14. Resource optimization in reflective intelligent surface (RIS)-aided mmWave systems - p. 349 37. Abstract - p. 349 38. 14.1 Introduction - p. page349 39. 14.2 A conceptual example - p. 357 40. 14.3 RIS-mmWave: single-RIS single user - p. page356 41. 14.4 RIS-mmWave: single-RIS multiple users - p. 377 42. 14.5 RIS-mmWave: multiple-RISs multiple users - p. 376 43. 14.6 Concluding remarks - p. 381 44. Bibliography - p. 382 45. Chapter 15. Signaling and optimization in orthogonal time–frequency–space (OTFS) and related schemes - p. 383 46. Chapter 16. Optimization in MIMO integrated sensing and communications (ISAC) - p. 405 47. Chapter 17. Optimization in user-centric cell-free (UCCF) wireless networks - p. 427 48. Bibliography - p. 453 49. Index - p. 471
