— Low-Density Parity-Check (LDPC) codes are typically characterized by a relatively high-complexity description, since a considerable amount of memory is required in order to store their code description, which can be represented either by the connections of the edges in their Tanner graph or by the non-zero entries in their parity-check matrix (PCM). This problem becomes more pronounced for pseudo-random LDPC codes, where literally each non-zero entry of their PCM has to be enumerated, and stored in a look-up table. Therefore, they become inadequate for employment in memoryconstrained transceivers. Motivated by this, we are proposing a novel family of structured LDPC codes, termed as Multilevel Structured (MLS) LDPC codes, which benefit from reduced storage requirements, hardware-friendly implementations as well as from low-complexity encoding and decoding. Our simulation results demonstrate that these advantages accrue without any compromise in their attainable Bit Error Ratio (BE...