Abstract-We present a new multi-rate architecture for decoding irregular LDPC codes in IEEE 802.16e WiMax standard. The proposed architecture utilizes the value-reuse property of offset min-sum, block-serial scheduling of computations and turbo decoding message passing algorithm. The decoder has the following advantages: 55% savings in memory, reduction of routers by 50%, and increase of throughput by 2x when compared to the recent state-of-the-art decoder architectures.Index Terms-low-density parity-check (LDPC) codes, offset min-sum, on-the-fly computation, decoder architecture, layered decoding, turbo-decoding message passing, irregular LDPC,IEEE 802.16e.

This paper presents a novel belief propagation (BP) based decoding algorithm for polar codes. The proposed algorithm facilitates belief propagation by utilizing the specific constituent codes that exist in the factor graph, which results in an express journey (XJ) for belief information to propagate in each decoding iteration. In addition, this XJ-BP decoder employs a novel round-trip message passing scheduling method for the increased efficiency. The proposed method simplifies min-sum (MS) BP decoder by 40.6%. Along with the round-trip scheduling, the XJ-BP algorithm reduces the computational complexity of MS BP decoding by 90.4%; this enables an energy-efficient hardware implementation of BP decoding in practice.

No abstract

No abstract

This paper explores a novel receiver architecture for multiple-input multiple-output (MIMO) and orthogonal frequency division multiplexing (OFDM) based cognitive radio (CR) that utilizes compressive sensing (CS) technique. Assuming that a limited number of subcarriers are used simultaneously in one MIMO-OFDM channel, we show that the conventional MIMO receiver can be replaced with the proposed receiver to compressively sample signals. In the proposed reception architecture, signals from multiple antennas are mixed and sampled with less hardware by exploiting the sparsity in the OFDM channel usage. Applying the CS technology to the receiver directly reduces the power consumption in mixed signal circuit which is attributable to less number of analog-to-digital converters (ADCs). A new streamlined algorithm for digital signal processing (DSP) to recover the compressively sensed data is also devised. Besides the simplification of the signal sensing, the simulation results also show that the reception fidelity of the proposed architecture outperforms that of the conventional maximum likelihood (ML) MIMO detector when the channel is lightly loaded.