Adaptive Beamforming for Wireless Communications

Litva, J.; Sandhu, A.; Cho, K.; Lo, T.

doi:10.1007/978-1-4613-1331-1_10

Cited by 42 publications

(80 citation statements)

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“…Many estimation methods of wave number and DOA of signal sources can be found in [33][34][35]. Blind beamforming is another important beamforming technique, which does not require training sequences and any information concerning the array's geometries: for example, Constant Modulus Adaptive (CMA) beamforming in [36], Constant Modulus (CM) in [37], Spectrum self-COherent REstoral (SCORE) in [29][30][31][32][33][34][35][36][37][38][39] and Decision-Directed Algorithm (DDA) beamforming in [40,41]. To improve the robustness to the DOA uncertainty, the Bayesian beamformer was also proposed in [42,43].…”

Section: Uplink and Downlink Adaptive Beamforming For I-wimaxmentioning

confidence: 99%

Efficient Radio Transmission with Adaptive and Distributed Beamforming for Intelligent WiMAX

Lian

Nikookar

Ligthart

2011

Wireless Pers Commun

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In this paper, we introduce Adaptive Beamforming (AB) and Distributed Beamforming (DB) as two efficient techniques for Intelligent WiMAX (I-WiMAX). I-WiMAX is a new maritime communication system, consisting of Smart Radio (SR) principles and mobile WiMAX based on the IEEE 802.16e standard. Adopting AB, the same spectrum can accommodate more users by directing the main beam towards desired users while antenna pattern nulls towards others. To reduce the channel interferences caused by spectrum reusing, the Null Broadening (NB) method is required for downlink beamforming of I-WiMAX. A new NB method is presented in this paper with iterative weights computing for different OFDM subcarriers. Considering the spatial channel model seen at Subscriber Stations (SS) based on the von Mises distribution, the coverage range of one Base Station (BS) is dramatically enlarged by employing the NB technique. Meanwhile, assuming those SS which are within the coverage range as nodes of a relay network, the DB technique is introduced to forward signals to distant SS by forming the main beams towards them instead of deploying more BS to increase the communication range. It is proven in this paper that DB can successfully do the job. To reuse the spectrum, two DB methods are presented by directing different beams towards different required directions at the same time. With the AB and DB techniques, reliable I-WiMAX links can be established for long distances, with more optimum spectrum use and less infrastructure.

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Section: Uplink and Downlink Adaptive Beamforming For I-wimaxmentioning

confidence: 99%

Efficient Radio Transmission with Adaptive and Distributed Beamforming for Intelligent WiMAX

Lian

Nikookar

Ligthart

2011

Wireless Pers Commun

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“…Motivated by the demand for increasing throughput in wireless communication, antenna array assisted spatial processing techniques [1][2][3][4][5][6][7] have been developed in order to further improve the achievable spectral efficiency. In the uplink, the base station (BS) has the capacity to implement sophisticated receive (Rx) beamforming schemes to separate multiple user signals transmitted by mobile terminals (MTs).…”

Section: Introductionmentioning

confidence: 99%

Downlink MBER Transmit Beamforming Design Based on Uplink MBER Receive Beamforming for TDD-SDMA Induced MIMO Systems

Chen¹,

Yang²

2010

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The downlink minimum bit error rate (MBER) transmit beamforming is directly designed based on the uplink MBER receive beamforming solution for time division duplex (TDD) space-division multiple-access (SDMA) induced multiple-input multiple-output (MIMO) systems, where the base station (BS) is equipped with multiple antennas to support multiple single-antenna mobile terminals (MTs). It is shown that the dual relationship between multiuser detection and multiuser transmission can be extended to the rank-deficient system where the number of users supported is more than the number of transmit antennas available at the BS, if the MBER design is adopted. The proposed MBER transmit beamforming scheme is capable of achieving better performance over the standard minimum mean square error transmit beamforming solution with the support of low-complexity and high power-efficient MTs, particularly for rank-deficient TDD-SDMA MIMO systems. The robustness of the proposed MBER transmit beamforming design to the downlink and uplink noise or channel mismatch is investigated using simulation.

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“…On the other hand, blind adaptive algorithms do not require prior training, and hence they are referred to as "blind" algorithms. These algorithms attempt to extract salient characteristic of the transmitted signal in order to separate it from other users in the surrounding environment [2]. In this chapter we propose a technique that could be used with the blind or non blind algorithms to enhance their performance.…”

Section: Introductionmentioning

confidence: 99%