The Experts below are selected from a list of 43215 Experts worldwide ranked by ideXlab platform
Hui Liu - One of the best experts on this subject based on the ideXlab platform.
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downlink radio resource allocation for multi cell ofdma system
IEEE Transactions on Wireless Communications, 2006Co-Authors: Hui LiuAbstract:This paper presents a radio resource control (RRC) scheme for OFDMA systems where dynamic resource allocation is realized at both a radio network controller (RNC) and base stations (BSs). The scheme is semi-distributed in the sense that the RRC decision is split between RNC and BSs. RNC makes decision on which Channel is used by which BS at super-frame level and BSs then make decision on which user is assigned to which Channel at frame-level. Two optimization problems for RNC and BSs are formulated and computationally efficient algorithms that perform the function of interference avoidance and Traffic/Channel adaptation are developed. Numerical analysis is performed under several cell configurations to show tradeoffs between sector interference suppression and dynamic interference avoidance. The results indicate that with reasonable signaling overhead, the protocol and the associated algorithms yield excellent performance for both real-time and non real-time services, even under fast fading
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ofdm based broadband wireless networks design and optimization
2005Co-Authors: Hui LiuAbstract:Preface. 1. Introduction. 1.1 OFDM-based wireless network overview. 1.1.1 Digital broadcasting and DVB-T. 1.1.2 Wireless LAN and IEEE 802.11. 1.1.3 WiMAX and IEEE 802.16. 1.2 The need for "cross-layer" design. 1.3 Organization of this text. 2. OFDM Fundamentals. 2.1 Broadband radio Channel characteristics. 2.1.1 Envelope fading. 2.1.2 Time dispersive Channel. 2.1.3 Frequency dispersive Channel. 2.1.4 Statistical characteristics of broadband Channels. 2.2 Canonical form of broadband transmission. 2.3 OFDM realization. 2.4 Summary. 3. PHY Layer Issues - System Imperfections. 3.1 Frequency synchronization. 3.1.1 OFDM carrier offset data mode. 3.1.2 Pilot-based estimation. 3.1.3 Non-pilot based estimation. 3.2 Channel estimation. 3.2.1 Pilots for 2D OFDM Channel estimation . 3.2.2 2DMMSE Channel estimation. 3.2.3 Reduced complexity Channel estimation. 3.3 I/Q imbalance compensation. 3.3.1 I/Q Imbalance Model. 3.3.2 Digital compensation receiver. 3.3.3 Frequency offset estimation with I/Q imbalance. 3.4 Phase noise compensation. 3.4.1 Mathematical models for phase noise. 3.4.2 CPE estimation with Channel state information. 3.4.3 Time domain Channel estimation in the presence of CPE. 3.4.4 CPE estimation without explicit CSI. 3.5 Summary. 4. PHY Layer Issues - Spatial Processing. 4.1 Antenna array fundamentals. 4.2 Beam forming. 4.2.1 Coherent combining. 4.2.2 Zero-forcing. 4.2.3 MMSE reception (optimum linear receiver). 4.2.4 SDMA. 4.2.5 Broadband beam forming. 4.3 MIMO Channels and capacity. 4.4 Space-time coding. 4.4.1 Spatial multiplexing. 4.4.2 Orthogonal space-time block coding. 4.4.3 Concatenated ST transmitter. 4.4.4 Beam forming with ST coding. 4.4.5 ST beam forming in OFDM. 4.5 Wide-area MIMO beam forming. 4.5.1 Data model. 4.5.2 Uncoded OFDM design criterion. 4.5.3 Coded OFDM design criterion. 4.6 Summary. 4.7 Appendix I: Derivation of Pe. 4.8 Appendix II: Proof of Proposition 5. 4.9 Appendix III: Proof of Proposition 6. 5. Multiple Access Control Protocols. 5.1 Introduction. 5.2 Basic MAC protocols. 5.2.1 Contention based protocols. 5.2.2 Non-contention based MAC protocols. 5.3 OFDMA advantages. 5.4 Multiuser diversity. 5.5 OFDMA optimality. 5.5.1 Multiuser multicarrier SISO systems. 5.5.2 Multiuser multicarrierMIMO systems. 5.6 Summary. 5.7 Appendix I: Cn(p) is a convex function in OFDMA/SISO case. 5.8 Appendix II: C(p) is a convex function in OFDMA/MIMO case. 6. OFDMA Design Considerations. 6.1 Cross layer design introduction. 6.2 Mobility-dependent OFDMA Traffic Channels. 6.2.1 OFDMA Traffic Channel. 6.2.2 System model. 6.2.3 Channel configuration for fixed/portable applications. 6.2.4 Channel configuration for mobile application. 6.3 IEEE 802.16e Traffic Channels. 6.4 Summary. 7. Frequency Planning in Multi-cell Networks. 7.1 Introduction. 7.1.1 Fixed Channel allocation. 7.1.2 Dynamic Channel allocation. 7.2 OFDMA DCA. 7.2.1 Protocol design. 7.2.2 Problem formulation for the RNC. 7.2.3 Problem formulation for BSs. 7.2.4 Fast algorithm for the RNC. 7.2.5 Fast algorithm for BSs. 7.3 Spectrum efficiency under different cell/sector configurations. 7.3.1 System configuration and signaling overhead. 7.3.2 Channel loading gains. 7.4 Summary. 8. Appendix. 8.1 IEEE 802.11 and WiFi. 8.1.1 802.11 overview. 8.1.2 802.11 network architecture. 8.1.3 The MAC layer technologies. 8.1.4 The physical layer technologies. 8.2 IEEE 802.16e and Mobile WiMAX. 8.2.1 Overview. 8.2.2 The physical layer technologies. 8.2.3 The MAC layer technologies. 8.3 Performance analysis of WiMAX systems. 8.3.1 WiMAX OFDMA-TDD. 8.3.2 Comparison Method. Notations and Acronym. About the Authors. Index.
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effect of Traffic Channel configuration on the orthogonal frequency division multiple access downlink performance
IEEE Transactions on Wireless Communications, 2005Co-Authors: Manyuan Shen, Hui LiuAbstract:This paper studies Traffic Channel design tradeoffs for downlink orthogonal frequency division multiple access (OFDMA) systems. For fixed and portable users where the propagation Channels are quasistatic, we show that the aggregated rate can be maximized by exploiting "multiuser diversity" through intelligent Channel allocation. In this case, the Traffic Channel should be configured so that its corresponding achievable data rate has the highest variance among users. The capacity upper and lower bounds are derived to quantify the impact of different Traffic Channel configurations. For mobile services where multiuser diversity cannot be efficiently exploited due to the signaling overhead, we show that the system outage capacity is maximized when the Traffic Channels are configured with maximum frequency diversity. Using the results presented, designers of OFDMA system can determine the optimum Traffic Channel configuration based on the types of services supported by the network.
D C Cox - One of the best experts on this subject based on the ideXlab platform.
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performance improvement with random insertion of power control bits in a cdma forward Traffic Channel
Vehicular Technology Conference, 2002Co-Authors: H Moon, D C CoxAbstract:In a forward Traffic Channel of an IS-95 system, coded symbols are randomly punctured after interleaving to transmit power control bits for the reverse Channel. The random puncturing results in performance degradation of the forward link and a frame error rate floor even on an AWGN Channel. This paper proposes a new scheme to transmit the power control bits in a CDMA forward Traffic Channel. To compare the performance of the multiplexing schemes, we present a method to compute the upper bound on the frame error rate of convolutional codes. By numerical analysis and simulations, we show that the performance of the proposed scheme is better than that of the random puncturing used in the IS-95 system.
S Uppala - One of the best experts on this subject based on the ideXlab platform.
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designing a mobile broadband wireless access network
IEEE Signal Processing Magazine, 2004Co-Authors: R Laroia, S UppalaAbstract:In this paper, a new OFDM-based air interface technology for a mobile broadband wireless system is described. The technology leverages the standard Internet protocol (IP) network elements to build the system and deploys a new air interface technology based on OFDMA. Cross-layer optimization played a major role in the design where the choices made in the physical, MAC, and link layers are also driven by the goal of extending the Internet to the wireless space. A major physical layer benefit of this air interface comes from the orthogonality property that the results in the elimination of in-cell interference are averaged and a worst-case interferer does not limit the system performance. The physical layer features not only result in high capacity but also provide very fine granularity of allocating air link resources, which improves the MAC and link-layer efficiency. The MAC and link layer provide contention-free, fast control Channels between the RAR and the WTs. These Channels are used to ferry a variety of signaling such as assignments of Traffic Channel, acknowledgements, Channel quality, and Traffic request reports. This holistic approach allows for a scheduler that could not only achieve high spectral efficiency but also allow for a fine control over QoS attributes such as latency, reliability, and service differentiation.
Sehyun Oh - One of the best experts on this subject based on the ideXlab platform.
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Performance analysis of Channel assignment methods for multiple carrier CDMA cellular systems
1999 IEEE 49th Vehicular Technology Conference (Cat. No.99CH36363), 1999Co-Authors: Bongyong Song, Sehyun OhAbstract:We analyze performance of two Channel assignment methods applicable to multiple carrier CDMA cellular systems. They are ICCA (independent carrier Channel assignment) method and CCCA (combined carrier Channel assignment) method. In ICCA, Traffic Channels of each carrier are handled independently so that each MS (mobile station) is allocated a Traffic Channel of the same carrier as is used in its idle state. In contrast, CCCA scheme combines all Traffic Channels in a system. When a BS (base station) receives a new call request, a BS searches least occupied carrier and allocates a Traffic Channel in that carrier. For the smooth handoff (soft handoff), carrier transition is not allowed for a handoff call. Performance measures considered are Erlang capacity, H/W resource utilization and cell coverage stability. It is shown that CCCA outperforms ICCA in each performance measure.
R Elliott - One of the best experts on this subject based on the ideXlab platform.
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comparative forward link Traffic Channel performance evaluation of hdr and 1xtreme systems
Vehicular Technology Conference, 2002Co-Authors: C H Rentel, Witold A Krzymien, B Darian, V Vanghi, R ElliottAbstract:This paper presents a comparison of the forward link performance of the HDR and 1XTREME systems. Both systems have been proposed as possible evolutionary paths for the 1.25 MHz cdma2000 system, and have been designed to enable high data rate packet transmission. Link-level performance is evaluated by chip-level time-domain simulation of the forward data Traffic Channel in the presence of additive white Gaussian noise, and is then used in a system-level simulator modeling a network of 19 three-sector cells. The system-level simulator accounts for slow and fast fading and two types of multipath Channel profiles, as described by the pedestrian A and vehicular B ITU-R Channel models. The packet scheduling is performed using a proportionally fair (PF) scheduler. The systems use bit rate adaptation and hybrid ARQ to achieve 1% packet error rate (PER). All users in the system are assumed to always have data packets available for transmission. System performance is evaluated for an embedded sector in terms of average sector throughput as a function of the number of users, distributions of data rates, and individual throughputs over a set of users. Results show the benefits of multiuser diversity exploited by the PF scheduler, and present throughput and fairness comparisons for the two systems.
