The cognitive multiple input multiple output( MIMO)network can utilize radio spectrum efficiently and satisfy the demand of high data rate. In order to decrease the interference during transmission,a new interference ...The cognitive multiple input multiple output( MIMO)network can utilize radio spectrum efficiently and satisfy the demand of high data rate. In order to decrease the interference during transmission,a new interference alignment( IA) algorithm based on cognitive MIMO networks is proposed in this paper. The algorithm is realized by designing two-level pre-coding, the first-level precoding aligns the interference generated by the cognitive users( CUs) to unused sub-channels of the primary user( PU),thereby eliminating the interference of CUs to PU; the second-level precoding is used to improve the throughput of CUs. Simulation shows that the proposed IA algorithm can eliminate the interference that the CUs produce on the PU and improve the throughput of CUs spontaneously.展开更多
The article investigates how to send perfect space-time codes with low feedback amount and symbol-by-symbol decoding for X channel using precoders. It is assumed that two users are introduced with two antennas and two...The article investigates how to send perfect space-time codes with low feedback amount and symbol-by-symbol decoding for X channel using precoders. It is assumed that two users are introduced with two antennas and two receivers. Each user employs a rate-2 space-time block code and follows certain rule when sending codewords. The multi-user interference is eliminated by pre-coding at the transmitter and linear processing at the receiver. Compared with the existing scheme for the same scene, the proposed scheme greatly reduces feedback amount and improves the transmission efficiency, while keeping the same decoding complexity. Simulations demonstrate the validity of the proposed scheme.展开更多
This paper mainly elaborates the studies of channel estimation and downlink data transmission in Massive MIMO. As there are different types of interference in single-cell and multi-cell systems, this paper establishes...This paper mainly elaborates the studies of channel estimation and downlink data transmission in Massive MIMO. As there are different types of interference in single-cell and multi-cell systems, this paper establishes different models for them separately. In terms of uplink training, for getting channel state information, we introduce LS and MMSE channel estimation algorithms and make a comparison between them. At the same time, the problem of pilot contamination is solved by cell classification and pilot identification. Next, this paper defines mathematical models for downlink data transmission. We use pre-coding methods (including Zero-forcing and Maximal Ratio Combining schemes) and optimize power distribution to improve channel capacity and transmission rate. Furthermore, this paper provides numerical results to show the simulation performance in both single-cell and multi-cell systems and extends to prospects in the future.展开更多
基金Innovation Program of Shanghai Municipal Education Commission,China(No.12ZZ126)the Program of Shanghai Normal University,China(No.DZL126)
文摘The cognitive multiple input multiple output( MIMO)network can utilize radio spectrum efficiently and satisfy the demand of high data rate. In order to decrease the interference during transmission,a new interference alignment( IA) algorithm based on cognitive MIMO networks is proposed in this paper. The algorithm is realized by designing two-level pre-coding, the first-level precoding aligns the interference generated by the cognitive users( CUs) to unused sub-channels of the primary user( PU),thereby eliminating the interference of CUs to PU; the second-level precoding is used to improve the throughput of CUs. Simulation shows that the proposed IA algorithm can eliminate the interference that the CUs produce on the PU and improve the throughput of CUs spontaneously.
基金supported by the National Natural Science Foundation of China (51174263)the Natural Science Foundation of Henan (132300410461)
文摘The article investigates how to send perfect space-time codes with low feedback amount and symbol-by-symbol decoding for X channel using precoders. It is assumed that two users are introduced with two antennas and two receivers. Each user employs a rate-2 space-time block code and follows certain rule when sending codewords. The multi-user interference is eliminated by pre-coding at the transmitter and linear processing at the receiver. Compared with the existing scheme for the same scene, the proposed scheme greatly reduces feedback amount and improves the transmission efficiency, while keeping the same decoding complexity. Simulations demonstrate the validity of the proposed scheme.
文摘This paper mainly elaborates the studies of channel estimation and downlink data transmission in Massive MIMO. As there are different types of interference in single-cell and multi-cell systems, this paper establishes different models for them separately. In terms of uplink training, for getting channel state information, we introduce LS and MMSE channel estimation algorithms and make a comparison between them. At the same time, the problem of pilot contamination is solved by cell classification and pilot identification. Next, this paper defines mathematical models for downlink data transmission. We use pre-coding methods (including Zero-forcing and Maximal Ratio Combining schemes) and optimize power distribution to improve channel capacity and transmission rate. Furthermore, this paper provides numerical results to show the simulation performance in both single-cell and multi-cell systems and extends to prospects in the future.
