科研之友
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摘要
MIMO (Multiple Input Multiple Output) techniques are widely employed to improve the performance of wireless systems. These techniques are used to overcome multipath fading and/or improve the peak throughput of wireless systems. It is well known that there is a fundamental tradeoff between diversity gain and multiplexing gain [1]. Orthogonal space time codes such as the Alamouti code (also known as space time block codes (STBC)) exploit multiple antennas as a diversity source, and thus improve packet error rate (PER) and the average throughput. However, space time block codes are not designed to increase the peak data rate of the system. On the other hand, spatial multiplexing (SM) techniques offer higher peak throughput by transmitting parallel streams of data from different antennas. In order to successfully decode the parallel streams, the channel must exhibit a small eigenvalue spread. Otherwise, the streams will interfere with one another and it is difficult to decode the information data. The performance improvement from SM is therefore highly dependent on the channel characteristics. It is possible to use multiple encoders and rate control per layer to improve the SM performance. However, there are instances of channel where STBC is more beneficial than SM with a single encoder. In order to resolve the shortcomings of STBC and SM, a hybrid technique can be applied where depending on the instantaneous channel conditions either STBC or SM is selected. This technique is commonly referred to as Adaptive MIMO Switching (AMS) [5]-[11]. One important aspect of the technique is the switching criteria, namely the PHY Abstraction method which estimates a packet error event as a function of the instantaneous channel condition, transmission profiles, and receiver characteristics. We show that the proposed algorithm outperforms other techniques such as determinant and Demmel condition number based techniques in flat fading channel. In selective fading channels where a codeword sees a finite number of multiple channel qualities, estimating the resulting PER is very challenging. Existing techniques rely on an estimate of the average of the channel qualities seen by each codeword. In this paper, we propose a PHY abstraction and switching algorithm hereby referred to by Weighted Sum of Instantaneous Qualities (WSIQ) whereby the channel qualities are ordered in order to reduce the variance of channel qualities and then a weighted sum of the qualities is applied. The weighting vector is chosen to minimize the variance of the linear sum. We have provided simulations to show the superiority of WSIQ even when channel statistics are unknown. In addition, computationally efficient techniques suited for practical implementation are proposed.
- 出版日期2008-8
