ITR/SI: Wireless Transmission Optimization for Bursty Data Traffic

预计无线通道将像有线互联网一样，在提供无缝信息的高速公路上发挥主导作用。未来，无线数据流量将越来越多地由各种多媒体主导，如实时视频、电子邮件、网络下载，而不是语音传输。信息技术研究计划设想的无绳通信和网络需要深入研究如何处理无线信道上的多媒体传输。各种多媒体具有与语音非常不同的业务特性，具有不同的延迟约束和突发。处理突发数据主要是在网络社区中解决的。社区关注的是业务延迟约束、分组丢失率(假设为分组丢失率)和信道容量之间的关系，这些都是通过测量“有效带宽”来获取的。有线(光纤、铜缆等)中的网络问题这种方法已经成功地解决了介质问题，因为该通道本质上是一个低差错通道。然而，网络社区基本上忽略了这样一个事实，即有一个非常真实的、非理想的物理通道来承载这些数据。因此，将这些方法迁移到无线介质遇到了一个重大障碍--无线信道本身就是一个非常嘈杂、不稳定的信道。因此，对于无线信道，重要的是考虑突发和信道差错对分组丢失的影响。研究人员一直在以一种特别的方式(PI认为)来考虑这两种影响。这项提案打算以系统和合乎逻辑的方式处理这一问题。具体地说，PI建议引入突发和信道状况的联合度量，并使用该度量来解决在无线系统的竞争用户之间分配稀缺资源的关键问题。拟议的联合方法是范式上的根本性变化，因为它试图综合网络和通信理论社区的想法。信源突发以及信道错误(由于噪声、衰落等)的原因影响信道容量的标准概念，是由于数据通信中有限延迟的要求。因此，PI制定了一套与延迟和丢包有关的初始措施(完整提案中的详细信息)。该方法基于信息论背景下发展起来的随机编码误差指数方法。为了降低丢包概率，无线发射机必须以尽可能高的数据速率进行传输。但是，由于传输错误，高传输速率将意味着无线信道上的高分组错误概率。PI制定的衡量标准试图捕捉到这种权衡。初步分析表明，对于衰落无线信道上的突发业务传输，使用该措施确实提供了实质性的好处(就设计最佳系统而言)。目前研究的第一步将是完善已开发的联合措施。这将涉及使用更复杂的源业务模型、更复杂的衰落信道模型和实用的信道编码方案。然后，开发的措施将被用于设计最优或稳健的方案(根据需要)，以将无线资源分配给竞争的数据流。这将涉及使用联合测量来开发调度流控制算法以及相关联的自适应信道编码方案。综上所述，本研究将为突发性数据流量在无线信道上的传输优化引入一种全新的范式，并在实际情况中展示新范式的有效性。

The wireless channel is expected to play as dominant a role as the wired internet, in providing seamless information 'super-highway'. In the future, wireless data traffic will be increasingly dominated by a variety of multimedia, such as real-time video, email, web downloads, as opposed to voice transmission. "Tether-free communication and networking', as envisioned by the Information Technology Research program, requires intensive research into handling the transmission of multimedia over the wireless channel. Various multimedia have very different traffic characteristics than voice, being characterized by different delay constraints and burstiness. Handling bursty data has been addressed primarily in the networking communit. The community has focussed on the relationship among the traffic delay constraint, the packet loss rate (which is assumed to be the packet drop rate), and the channel capacity, captured by measures such as "Effective bandwidth'. Networking problems in wired (fiber, copper, etc.) media have been successfully solved by this approach, because this channel is inherently a low-error channel. However, the networking community has by and large ignored the fact that there is a very real, non-idea physical channel on which this data is carried. Therefore, the migration of these approaches to the wireless medium meets a significant obstacle- the fact that the wireless channel is inherently a very noisy, non-robust channel. Thus for wireless channels, it is important to consider the effect on packet loss of both, burstiness and channel errors. Researchers have been approaching the issue of considering both these effects in (the PI believes) an ad hoc manner. This proposal intends to approach the issue in a systematic and logical manner. Specifically, the PI proposes to introduce a joint measure of burstiness and channel condition, and use the measure to solve the key problem of allocating scarce resources among competing users of a wireless system. The proposed joint approach is a fundamental change in paradigm, since it attempts to synthesize ideas from the Networking and Communication Theory communities. The reason why source burstiness as well as channel errors (due to noise, fading, etc.) affect the standard notions of channel capacity, is due to the requirement of finite delay in the data communication. The PI has therefore developed an initial set of measures (details in the full proposal) that relate the delay and packet loss. The measure is based on the random coding error exponent approach, developed in an information theoretic setting. To reduce the packet drop probability, the wireless transmitter must transmit at as high a data rate as possible. But a high rate of transmission would imply a high packet error probability on the wireless channel, due to transmission errors. The measure developed by the PI attempts to capture this trade-off. Preliminary analysis indicates that using this measure indeed offers a substantial benefit (in terms of designing an optimum system) for bursty traffic transmission over fading wireless channels. The first step in the current research would be to refine the developed joint measure. This would involve using more sophisticated source traffic models, more sophisticated fading channel models, and practical channel coding schemes. The developed measure will then be used to design optimal or robust schemes (as the need may be) to allocate wireless resources to competing streams of data traffic. This will involve developing scheduling flow control algorithms, and the associated adaptive channel coding schemes, using the joint measure. In summary, this research will introduce a fundamentally new paradigm for transmission optimization of bursty data traffic over wireless channels, and then demonstrate the usefulness of the new paradigm in practical situations.