With　the　exponential　growth　of　devices,　particularly　Internet　of　things　(IoT)　devices,　connecting　to　wireless　networks,　existing　networks　face　significant　challenges.　Spectral　efficiency　is　crucial　for　uplink,　which　is　the　dominant　form　of　asymmetrical　network　in　today＇s　communication　landscape,　in　large-scale　connectivity　scenarios.　In　this　paper,　an　uplink　transmission　scenario　is　considered　and　user　equipment　(UE)　aggregation　is　employed,　wherein　some　users　act　as　cooperative　nodes　(CNs),　and　help　to　forward　received　data　from　other　users　requiring　coverage　extension,　reliability　improvement,　and　data-rate　enhancement.　Non-orthogonal　multiple　access　(NOMA)　technology　is　introduced　to　improve　spectral　efficiency.　To　reduce　the　interference　impact　to　guarantee　the　data　rate,　one　UE　can　be　assisted　by　multiple　CNs,　and　these　CNs　and　corresponding　assisted　UEs　are　clustered　into　joint　transmission　pairs　(JTPs).　Interference-free　transmission　can　be　achieved　within　each　JTP　by　utilizing　different　successive　interference　cancellation　(SIC)　decoding　orders.　To　explore　SIC　gains　and　maximize　data　rates　in　NOMA-based　UE　aggregation,　we　propose　a　primary　user　CN-based　channel-sorting　algorithm　for　JTP　construction　and　apply　a　whale　optimization　algorithm　for　JTP　power　allocation.　Additionally,　a　conflict　graph　is　established　among　feasible　JTPs,　and　a　greedy　strategy　is　employed　to　find　the　maximum　weighted　independent　set　(MWIS)　of　the　conflict　graph　for　subchannel　allocation.　Simulation　results　demonstrate　that　our　joint　collaborative　NOMA　(JC-NOMA)　design　with　two-hop　multi-path　UE　aggregation　significantly　improves　spectral　efficiency　and　capacity　under　limited　spectral　resources.