Incremental redundancy hybrid automatic repeat request(IR HARQ) has been extensively studied for reliable data transmission over slow-fading or quasi-static channels.With the increase in movement speed of users and th...Incremental redundancy hybrid automatic repeat request(IR HARQ) has been extensively studied for reliable data transmission over slow-fading or quasi-static channels.With the increase in movement speed of users and the use of long code words for data transmission,IR HARQ strategy in fast-fading channels is starting to attract attention in the academia.This paper studies the performance of the IR HARQ strategy based on Kite codes(a class of rateless codes) in the finite regime over fast-fading channels where a number of channel realizations are experienced in each retransmission round.We propose an algorithm that exploits current decoding reliability to determine the size of subsequent retransmissions.Longterm throughput and delay constraint throughput are analyzed and compared.Furthermore,in HARQ systems available,most of the computation power is consumed on failed decoding if a code word is retransmitted many times,which is not energy-efficient.Therefore,to improve theenergy efficiency,we propose two efficient algorithms(early stopping algorithm and freezing node algorithm) for incremental decoding,which reduce the computational complexity of the most time-consuming steps in decoding procedure.Simulation results show that the substantial complexity reduction is achieved in terms of the total required number of decoding iterations and the required node operation complexity compared to conventional incremental decoding scheme.展开更多
A compressed sensing（CS） based channel estimation algorithm is proposed by using the delay-Doppler sparsity of the fast fading channel.A compressive basis expansion channel model with sparsity in both time and frequ...A compressed sensing（CS） based channel estimation algorithm is proposed by using the delay-Doppler sparsity of the fast fading channel.A compressive basis expansion channel model with sparsity in both time and frequency domains is given.The pilots in accordance with a novel random pilot matrix in both time and frequency domains are sent to measure the delay-Doppler sparsity channel.The relatively nonzero channel coefficients are tracked by random pilots at a sampling rate significantly below the Nyquist rate.The sparsity channels are estimated from a very limited number of channel measurements by the basis pursuit algorithm.The proposed algorithm can effectively improve the channel estimation performance when the number of pilot symbols is reduced with improvement of throughput efficiency.展开更多
基金supported in part by the National Basic Research Program of China(2012CB316100)the National Natural Science Foundation of China(61372074 and 61172082)National Key Laboratory Foundation of China(9140C530401120C53201)
文摘Incremental redundancy hybrid automatic repeat request(IR HARQ) has been extensively studied for reliable data transmission over slow-fading or quasi-static channels.With the increase in movement speed of users and the use of long code words for data transmission,IR HARQ strategy in fast-fading channels is starting to attract attention in the academia.This paper studies the performance of the IR HARQ strategy based on Kite codes(a class of rateless codes) in the finite regime over fast-fading channels where a number of channel realizations are experienced in each retransmission round.We propose an algorithm that exploits current decoding reliability to determine the size of subsequent retransmissions.Longterm throughput and delay constraint throughput are analyzed and compared.Furthermore,in HARQ systems available,most of the computation power is consumed on failed decoding if a code word is retransmitted many times,which is not energy-efficient.Therefore,to improve theenergy efficiency,we propose two efficient algorithms(early stopping algorithm and freezing node algorithm) for incremental decoding,which reduce the computational complexity of the most time-consuming steps in decoding procedure.Simulation results show that the substantial complexity reduction is achieved in terms of the total required number of decoding iterations and the required node operation complexity compared to conventional incremental decoding scheme.
基金supported by the National Natural Science Foundation of China(60972056)the Innovation Foundation of Shanghai Education Committee(09ZZ89)Shanghai Leading Academic Discipline Project and STCSM(S30108and08DZ2231100)
文摘A compressed sensing（CS） based channel estimation algorithm is proposed by using the delay-Doppler sparsity of the fast fading channel.A compressive basis expansion channel model with sparsity in both time and frequency domains is given.The pilots in accordance with a novel random pilot matrix in both time and frequency domains are sent to measure the delay-Doppler sparsity channel.The relatively nonzero channel coefficients are tracked by random pilots at a sampling rate significantly below the Nyquist rate.The sparsity channels are estimated from a very limited number of channel measurements by the basis pursuit algorithm.The proposed algorithm can effectively improve the channel estimation performance when the number of pilot symbols is reduced with improvement of throughput efficiency.
