Grant Free Multiple Access For Future Massive-IoT Communications
Creators: name: Gao, Pengyu
Publisher: name: University of Surrey
Year: 2024
Subjects: Grant-free multiple access (GF-MA)
non-orthogonal multiple access (NOMA)
compressed sensing (CS)
multi-user detection (MUD)
uncoordinated random access (URA)
sparse code multiple access (SCMA)
power domain nonorthogonal multiple access (PD-NOMA)

description: By reducing the complicated signaling overhead, grant-free multiple access (GF-MA)technique is deemed as a promising uplink access solution in future massive Internetof-Things (IoT) communications. In this thesis, grant-free non-orthogonal multipleaccess (GF-NOMA) techniques are investigated, which enable massive connectivitywith low access latency. In particular, two types of GF-NOMA techniques are studied,contention-free and contention-based, respectively. Specifically, in contention-freeGF-NOMA schemes, each user is pre-allocated a unique signature sequence for the incominguplink access. At the receiver, compressed sensing (CS) theory is applied tocarry out user activity identification and data detection, by taking advantage of thesporadic transmission feature. On the other hand, contention-based GF-MA schemes,also known as uncoordinated random access (URA) schemes, allow for an arrive-andgouplink access manner, without the need for prior coordination and resource preallocation.However, due to the lack of central coordination, when multiple users selectthe same resource block to transmit simultaneously, frequent collisions lead to low systemthroughput, which becomes the bottleneck. The integration of NOMA techniquescan alleviate these impediments, thereby enhancing system spectrum efficiency.The thesis contains four technical chapters. The first two contributions aim at thedesign of low-complexity CS-based MUD design in the contention-free GF-NOMA systems,while the remaining two focus on the performance analysis and traffic load regulationin contention-based GF-NOMA systems.In the first work, we propose a low-complexity CS-based sparsity adaptive block gradientpursuit (SA-BGP) algorithm in uplink GF-NOMA systems. The proposed SA-BGPalgorithm is capable of jointly carrying out channel estimation, user activity detectionand data detection without knowing the user sparsity level. By exploiting the inherentsparsity of transmission signal and gradient descend, the proposed method enjoys agood detection performance with substantial reduction of computational complexity.In the second work, block coordinate descend (BCD) method is employed in uplink GFNOMAsystems, aiming at reducing the computational complexity of the CS-MUD. Wedesign two modified BCD based algorithms, called enhanced BCD (EBCD) and complexityreduction enhanced BCD (CR-EBCD), respectively. In particular, by incorporatinga novel candidate set pruning mechanism into the original BCD framework, theproposed EBCD algorithm achieves remarkable CS-MUD performance improvement. Inaddition, the proposed CR-EBCD algorithm further ameliorates the proposed EBCDby eliminating the redundant matrix multiplications during the iteration process. Consequently,compared with the proposed EBCD algorithm, the proposed CR-EBCDalgorithm enjoys two orders of magnitude complexity saving without sacrificing anyCS-MUD performance, rendering it a viable solution for future massive machine-typecommunication (mMTC) scenarios.In the third work, a novel uplink URA protocol is proposed, which integrates with sparsecode multiple access (SCMA) technique, referred to as SCMA-aided slotted-ALOHA(S-ALOHA) scheme. Specifically, each active user transmits an SCMA codeword tothe access point (AP) in an arbitrary time slot whenever they want without the need of prior scheduling. However, due to the lack of central management in the proposedURA-based scheme, codebook collisions become inevitable, making the decoding challengingat the AP. To cope with this issue, we propose an interference-canceling (IC)first decoding strategy at the AP, which is able to partially address collision problems,contributing to a higher system throughput. For the proposed IC-first decoding strategy,a theoretical expression of the throughput has been derived. Moreover, to alleviatethe throughput degradation under the congested user traffic, a user barring mechanismis introduced to control the traffic load. Based on the estimated real-time load, theAP adaptively adjusts the access probability and redistributes the actual access load.Thus, the system throughput can maintain steadily close to the maximum value.In the fourth work, an efficient URA scheme with power domain non-orthogonal multipleaccess (PD-NOMA), namely PD-NOMA aided multi-channel slotted ALOHA (MSALOHA),is investigated. We first analytically study the throughput performance andpropose a more accurate theoretical bound for the system throughput, compared tothe existing results. Then, the idle subchannel probability, which can be used to indicatethe real-time traffic load, is reformulated by analysing the observable non-utilizedpower level (ONU-PL) and a concise analytical expression is further derived. Furthermore,in order to effectively manage the challenges posed by congested traffic loads, auser load control mechanism is introduced. This mechanism is devised to ensure thatthe real-time traffic load remains in close proximity to the optimal level by adaptivelycontrolling the user access probability, leading to a stable system throughput.