“…The algorithm's goal is to determine the groups, which will be served simultaneously, and the corresponding transmit power to minimize the ratio of occupied to Algorithm 2: Modified Incremental Multicast Grouping [17], L ≥ 1 available resources. Thus, the algorithm works until all groups are deleted from S M (lines [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22]. We also use D (m) to denote a set of groups to be served at a time slot m. The algorithm selects the worst (in the sense of the needed power) group from S M and adds this group to set D (m) (lines 7-9).…”
Section: Beam Assignment and Power Allocationmentioning
confidence: 99%
“…Finally, the computational complexity of Algorithm 3 is O(KL), where K is the complexity due to the "while" cycle over all n groups (with max K) in the worst case of the single group transmissions (lines [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22]. For the second component, which is inside the "while" cycle, L − 1 is the complexity due to the possible selection of simultaneous groups (lines [11][12][13][14][15][16][17][18].…”
Section: Complexity Analysismentioning
confidence: 99%
“…Multicasting is a prominent technique applied to improve bandwidth efficiency compared to unicast transmission [6], [7]. In the multicast regime, a base station (BS) can transmit the packet to many users simultaneously using the same band and modulation and coding scheme (MCS).…”
The support of multicast communications in the fifth-generation (5G) New Radio (NR) system poses unique challenges to system designers. Particularly, the highly directional antennas do not allow to serve all the user equipment devices (UEs) that belong to the same multicast session in a single transmission. However, the capability of modern antenna arrays to utilize multiple beams simultaneously, with potentially varying half-power beamwidth, adds a new degree of freedom to the UE scheduling. This work addresses the challenge of optimal multicasting in 5G millimeter wave (mmWave) systems by presenting a globally optimal solution for multi-beam antenna operation. The optimization problem is formulated as a special case of multiperiod variable cost and size bin packing problem that allows to not impose any constraints on the number of the beams and their configurations. We also propose heuristic solutions having polynomial time complexity. Our results show that for small cell radii of up to 100 meters, a single beam is always utilized. For higher cell coverage and practical ranges of the number of users (5-50), the optimal number of beams is upper bounded by 3.
“…The algorithm's goal is to determine the groups, which will be served simultaneously, and the corresponding transmit power to minimize the ratio of occupied to Algorithm 2: Modified Incremental Multicast Grouping [17], L ≥ 1 available resources. Thus, the algorithm works until all groups are deleted from S M (lines [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22]. We also use D (m) to denote a set of groups to be served at a time slot m. The algorithm selects the worst (in the sense of the needed power) group from S M and adds this group to set D (m) (lines 7-9).…”
Section: Beam Assignment and Power Allocationmentioning
confidence: 99%
“…Finally, the computational complexity of Algorithm 3 is O(KL), where K is the complexity due to the "while" cycle over all n groups (with max K) in the worst case of the single group transmissions (lines [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22]. For the second component, which is inside the "while" cycle, L − 1 is the complexity due to the possible selection of simultaneous groups (lines [11][12][13][14][15][16][17][18].…”
Section: Complexity Analysismentioning
confidence: 99%
“…Multicasting is a prominent technique applied to improve bandwidth efficiency compared to unicast transmission [6], [7]. In the multicast regime, a base station (BS) can transmit the packet to many users simultaneously using the same band and modulation and coding scheme (MCS).…”
The support of multicast communications in the fifth-generation (5G) New Radio (NR) system poses unique challenges to system designers. Particularly, the highly directional antennas do not allow to serve all the user equipment devices (UEs) that belong to the same multicast session in a single transmission. However, the capability of modern antenna arrays to utilize multiple beams simultaneously, with potentially varying half-power beamwidth, adds a new degree of freedom to the UE scheduling. This work addresses the challenge of optimal multicasting in 5G millimeter wave (mmWave) systems by presenting a globally optimal solution for multi-beam antenna operation. The optimization problem is formulated as a special case of multiperiod variable cost and size bin packing problem that allows to not impose any constraints on the number of the beams and their configurations. We also propose heuristic solutions having polynomial time complexity. Our results show that for small cell radii of up to 100 meters, a single beam is always utilized. For higher cell coverage and practical ranges of the number of users (5-50), the optimal number of beams is upper bounded by 3.
“…In [13], we discussed the necessary improvements of the SC-PTM service announcement and proposed a new grouping solution for the multicast reception of critical content, considering the drawbacks of the strategies from [11]. In the new strategy, the network schedules SC-PTM transmissions in a fixed interval named critical interval.…”
Section: Related Work and Contribution Of This Papermentioning
confidence: 99%
“…We also discuss minor but necessary changes in some messages of the RA stage, not addressed in [13].…”
Section: Related Work and Contribution Of This Papermentioning
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