Edward W. Jang

Handover in multihop cellular networks

This article introduces various handover scenarios in multihop cellular networks. In addition, this article presents handover schemes where relay stations are located either inside a cell or on the boundary between two adjacent cells and investigates the effects of the deployment position of relay stations to handover performance. The simulation results show that multihop cellular networks for both deployment scenarios can achieve 90 percent throughput increase over single-hop cellular networks. The results also show that the overall throughput of the multihop cellular networks with relay stations inside a cell is higher than for those with relay stations on the boundary between two adjacent cells, whereas the opposite is observed for the throughput of cell-boundary users. The intercell handover latency in multihop cellular networks is increased by 20 ~ 56 percent compared with that in single-hop cellular networks because of the increased number of handovers and signaling overhead. However, by deploying relay stations on the boundary between two adjacent cells, the service-interruption time caused by inter-cell handover is reduced by 80 percent compared with that of single-hop cellular networks.

Optimal Combining Schemes for MIMO Systems with Hybrid ARQ

This paper proposes and analyzes receiver schemes for multiple-input multiple-output (MIMO) systems with hybrid automatic-repeat-request (HARQ). It is shown by means of analysis as well as computer simulations that the proposed receiver schemes have optimal decoding performance in the sense that all the relevant information is fully used. Also complexity-wise, the proposed receiver schemes are found beneficial when designing MIMO systems, because the same decoding architecture can be re-used regardless of the number of retransmissions.

On the combining schemes for MIMO systems with hybrid ARQ

Multiple-input multiple-output (MIMO) systems with hybrid automatic-repeat-request (HARQ) promises high throughput with high reliability. However, combining-scheme design for such systems faces challenges, the presence of interference and the existence of multiple signal-to-interference-and-noise power ratios (SINRs). To overcome these challenges, this paper suggests to design combining schemes with the objective of directly optimizing the log-likelihood ratio (LLR) values. Using this approach, this paper proposes several combining schemes and then analyzes them based on three key design factors: decoding performance, scalability, and memory requirement. Computer simulations under the IEEE 802.16e standard settings show the performances of the proposed combining schemes, which align well with the analysis. Based on the analyses and the simulation results, this paper suggests preferable combining schemes respectively for MIMO systems with HARQ-chase combining (HARQ-CC) and HARQ-incremental redundancy (HARQ-IR).

Transceiver design for MIMO wireless systems incorporating hybrid ARQ

Hybrid ARQ, an extension of ARQ that incorporates forward error correction coding, is a retransmission scheme employed in current communications systems. The use of HARQ can contribute to efficient utilization of the available resources and the provision of reliable services in latest-generation systems. This article focuses on wireless systems using HARQ with emphasis on the multiple-input multiple-output paradigm. MIMO-HARQ offers new opportunities because of the additional degrees of freedom introduced by the multiple antennas at the transmitter and receiver. The architecture of MIMO transceivers that are based on bit-interleaved coded modulation and employ HARQ is described. Additionally, receiver implementations are presented and compared in terms of complexity, memory requirements, and performance.

Concatenation-Assisted Symbol-Level Combining Scheme for MIMO Systems with Hybrid ARQ

This paper proposes a new receiver scheme for multiple-input multiple-output (MIMO) systems with hybrid automatic-repeat-request (HARQ). The proposed scheme is proved to have the optimal decoding performance in a sense that all the relevant information is fully used for decoding. Furthermore, it is shown that the proposed scheme has reduced complexity compared to the other optimal receiver scheme. Simulation results under IEEE 802.16e setting with UMTS channel model verify that the proposed receiver scheme achieves the same decoding performance with the other optimal receiver scheme and performs better than other suboptimal receiver schemes.

DFE-Based Receiver Implementation for MIMO Systems Employing Hybrid ARQ

The implementation of decision feedback equalization-based receivers for MIMO systems that employ hybrid ARQ (HARQ) is considered. It is shown how the theory of MIMO decision feedback equalization can be applied to derive optimal DFE architectures for the case of MIMO HARQ. Incremental structures are proposed that reduce the implementation complexity of the DFE and the memory requirements at the receiver without loss in performance. Moreover, sub-optimal, post-equalization combining architectures are examined that simplify the receiver at the cost of performance loss.

Predetermined Power Allocation for Opportunistic Beamforming with Limited Feedback

This paper proposes an enhanced opportunistic beamforming scheme with power allocation search algorithms over finite feedback channels for a broadcast channel. Instead of continually varying the power allocation for multiple beams based on instantaneous channel state information (CSI) feedback, the proposed scheme determines power allocation in advance solely based on channel statistics and the number of mobile stations (MSs). This scheme maintains power allocation throughout multiple training and data transmission periods as long as channel statistics and the number of MSs are unchanged. As a result, the proposed scheme reduces the complexity for searching power allocation, and becomes robust over finite feedback channels. Computer simulations show that the proposed power allocation search algorithms efficiently find the near optimal power allocation with low complexity. The simulations also show that, although the proposed scheme predetermines power allocation solely based on channel statistics and the number of MSs, it outperforms the opportunistic beamforming scheme using instantaneous CSI feedback with finite feedback rates.

An efficient symbol-level combining scheme for MIMO systems with hybrid ARQ

This paper proposes a new combining scheme for multiple-input multiple-output (MIMO) systems with hybrid automatic-repeat-request (HARQ). The proposed combining scheme is proved to have the optimal decoding performance. Furthermore, the proposed combining scheme is shown to have low memory requirement and reduced complexity compared to other optimal combining schemes. Simulation results under IEEE 802.16e setting with UMTS channel models verify that the proposed combining scheme achieves the optimal decoding performance and performs much better than other suboptimal combining schemes.

Scheduling Algorithms for Time-Varying Downlink Channels

To maximize the spectral efficiency for a time- varying downlink channel with multiple users, the scheduling order of the users needs to be optimized. The scheduling problem naturally is a combinatorial optimization problem with high complexity, which exponentially increases with the number of users. This paper proposes several low-complexity scheduling algorithms. Computer simulation results show that the proposed algorithms approach optimal performance.

Improved OSIC decoder for spatially multiplexed system

This paper proposes to use candidate symbol table for the decoding of the first few substreams for spatially multiplexed system. In the new decoding algorithm, we generate candidate symbol table (CST) and do ordered successive interference cancellation (OSIC) for each candidates. At the end, Maximum Likelihood (ML) criteria is used to determine the optimum transmit symbol vector among the estimated candidates. Simulation result shows that the size of CST can be maintained to be small, even if the number of bits per symbol increases. Simulation results show that this algorithm gives us performance close to ML decoder, and outperforms maximum likelihood decision feedback equalizer (ML-DFE) and channel-based adaptive group detection based OSIC (AGD-OSIC).