Distributed Adaptation of Quantized Feedback for Downlink Network MIMO Systems

Distributed Adaptation of Quantized Feedback for Downlink Network MIMO Systems

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Abstract:

This paper focuses on quantized channel state information (CSI) feedback for downlink network MIMO systems. Specifically, we propose to quantize and feedback the CSI of a subset of BSs, namely the feedback set. Our analysis reveals the tradeoff between better interference mitigation with large feedback set and high CSI quantization precision with small feedback set. Given the number of feedback bits and instantaneous/long-term channel conditions, each user optimizes its feedback set distributive according to the expected SINR derived from our analysis. Simulation results show that the proposed feedback adaptation scheme provides substantial performance gain over non-adaptive schemes, and is able to effectively exploit the benefits of network MIMO under various feedback bit budgets.

Existing System:

   In Every signal propagates from the transmitter to the receiver and represents the combined effect of, for example, scattering, fading, and power decay with distance. The CSI makes it possible to adapt transmissions to current channel conditions, which is crucial for achieving reliable communication with high data rates in multiantenna systems.

Proposed System:

We propose to quantize and feedback the CSI of a subset of BSs, namely the feedback set. Our analysis reveals the tradeoff between better interference mitigation with large feedback set and high CSI quantization precision with small feedback set. Given the number of feedback bits and instantaneous/long-term channel conditions, each user optimizes its feedback set distributive according to the expected SINR derived from our analysis. Simulation results show that the proposed feedback adaptation scheme provides substantial performance gain over

Non-adaptive schemes, and is able to effectively exploit the benefits of network MIMO under various feedback bit budgets.

Modules:

1.     Channel State Information

2.     Clustered N/w MIMO Co-Ordination

3.     CSI Feedback

4.     Simulation Results

Channel State Information (CSI):

          In this Module quantized channel state information (CSI) feedback for downlink network MIMO systems. In Every signal propagates from the transmitter to the receiver and represents the combined effect, CSI needs to be estimated at the receiver and usually quantized and feed back to the transmitter (although reverse - link estimation is possible in TDD systems). Therefore, the transmitter and receiver can have different CSI. The CSI at the transmitter and the CSI at the receiver are sometimes referred to as CSIT and CSIR, respectively.

Clustered N/W MIMO Co-Ordination:

     In this module, the downlink of a cellular network with universal frequency reuse, where each BS is equipped with antennas and each user has a single antenna. The whole network is divided into disjointing cell clusters, i.e., each BS belongs to one cluster and each user is served by one cluster.

CSI FeedBack:

        In this Module, a CSI feedback set adaptation scheme is proposed to enhance system performance under feedback bit constraints. CSI feedback set adaptation is proposed, i.e., the equivalent channel vector ??  with any subset of the BSs.

Simulation Results:

       In this Module, A simulation  cellular network is tested , where each hexagonal cell has 3 collocated BSs. Each BS corresponds to a 120-degree sector , and the antenna angular pattern , where ?? is the angle with respected to the antenna broadside direction. The path-loss exponent is 3.5,One simulation includes 80 topology drops, and in every drop 20 users are randomly distributed in each cell. Multiuser proportional fair scheduling (MPFS) is executed, where we use a greedy user selection algorithm  with weighted sum-rate as optimization object, i.e., the weight ???? = 1/????, where ???? is the average throughput perceived by user ?? up tolast time slot, and is updated with fairness factor ?? = 10(time slots). Then power allocation is adopted to maximize the weighted sum-rate of the scheduled users in cluster ??.

System Requirements:

Hardware Required:                            

 System               :   Pentium IV 2.4 GHz

 Hard Disk          :   40 GB

 Floppy Drive      :   1.44 MB

 Monitor             :   15 VGA color

 Mouse                :   Logitech.

 Keyboard           :   110 keys enhanced

 RAM                 :   256 MB

Software Required:

 O/S                   :   Windows XP.

Language        :   Asp.Net, c#.

Data Base       :   Sql Server 2005.

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