ترغب بنشر مسار تعليمي؟ اضغط هنا

An Explicit Formula for the Zero-Error Feedback Capacity of a Class of Finite-State Additive Noise Channels

91   0   0.0 ( 0 )
 نشر من قبل Amir Saberi
 تاريخ النشر 2020
  مجال البحث الهندسة المعلوماتية
والبحث باللغة English




اسأل ChatGPT حول البحث

It is known that for a discrete channel with correlated additive noise, the ordinary capacity with or without feedback both equal $ log q-mathcal{H} (Z) $, where $ mathcal{H}(Z) $ is the entropy rate of the noise process $ Z $ and $ q $ is the alphabet size. In this paper, a class of finite-state additive noise channels is introduced. It is shown that the zero-error feedback capacity of such channels is either zero or $C_{0f} =log q -h (Z) $, where $ h (Z) $ is the {em topological entropy} of the noise process. A topological condition is given when the zero-error capacity is zero, with or without feedback. Moreover, the zero-error capacity without feedback is lower-bounded by $ log q-2 h (Z) $. We explicitly compute the zero-error feedback capacity for several examples, including channels with isolated errors and a Gilbert-Elliot channel.



قيم البحث

اقرأ أيضاً

The zero-error feedback capacity of the Gelfand-Pinsker channel is established. It can be positive even if the channels zero-error capacity is zero in the absence of feedback. Moreover, the error-free transmission of a single bit may require more tha n one channel use. These phenomena do not occur when the state is revealed to the transmitter causally, a case that is solved here using Shannon strategies. Cost constraints on the channel inputs or channel states are also discussed, as is the scenario where---in addition to the message---also the state sequence must be recovered.
157 - Jialing Liu , Nicola Elia , 2010
In this paper, we propose capacity-achieving communication schemes for Gaussian finite-state Markov channels (FSMCs) subject to an average channel input power constraint, under the assumption that the transmitters can have access to delayed noiseless output feedback as well as instantaneous or delayed channel state information (CSI). We show that the proposed schemes reveals connections between feedback communication and feedback control.
The capacity-achieving input distribution of the discrete-time, additive white Gaussian noise (AWGN) channel with an amplitude constraint is discrete and seems difficult to characterize explicitly. A dual capacity expression is used to derive analyti c capacity upper bounds for scalar and vector AWGN channels. The scalar bound improves on McKellips bound and is within 0.1 bits of capacity for all signal-to-noise ratios (SNRs). The two-dimensional bound is within 0.15 bits of capacity provably up to 4.5 dB, and numerical evidence suggests a similar gap for all SNRs.
The error exponent of Markov channels with feedback is studied in the variable-length block-coding setting. Burnashevs classic result is extended and a single letter characterization for the reliability function of finite-state Markov channels is pre sented, under the assumption that the channel state is causally observed both at the transmitter and at the receiver side. Tools from stochastic control theory are used in order to treat channels with intersymbol interference. In particular the convex analytical approach to Markov decision processes is adopted to handle problems with stopping time horizons arising from variable-length coding schemes.
التعليقات
جاري جلب التعليقات جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا