Fundamental effective capacity limits of cognitive radio in fading environments with imperfect channel information

Abstract

In this paper, we analyze the effective capacity gains of opportunistic spectrum-sharing with imperfect channel information. We consider that a secondary user may access the spectrum allocated to a primary user as long as the average interference power, inflicted at the primary's receiver as an effect of the transmission of the secondary user, remains below predefined power limits. We consider partial channel information of the link between the secondary user transmitter and primary user receiver is available to the secondary user. We derive the optimal power allocation strategy to achieve the maximum effective capacity under Rayleigh fading with imperfect channel information. Finally, we also obtained expressions for the average expenditure-power required to achieve the effective capacity with channel estimation error variance. Numerical results are conducted to corroborate our theoretical results.

Effective Capacity in Wireless Networks: A Comprehensive Survey

“…However, other spectrum sensing approaches, such as QoS-aware, cooperative, and cyclostationary-based spectrum sensing have not been explored while taking into consideration the EC model. This gray-space utilization pattern of CRNs with the EC concept has also been used to develop various optimal resource allocation schemes with stringent-delay requirements [102], [110], [116], [124], [137], [153], [172], [237]. Among resource allocation strategy, problem of power allocation has been formulated and then solved by applying different optimization scenarios.…”

“…Hybrid CRNs Spectrum Sensing [143], [145], [148], [234]- [236] Various Fading Conditions [115], [128], [129] Resource Allocation [102], [110], [116], [124], [137], [153], [172], [237] Modulation Techniques [118], [120], [203] Relaying In CRNs [142], [158], [195] Spectrum Sensing [157], [198] Interference Constraints [155], [238] CRNs with MISO Systems [239] Channel Access Approaches [240], [241] Resource Allocation [37], [44], [58], [60], [103], [107], [177], [181], [202], [225], [242]- [245] Spectrum Sensing [15] Interference Constraints [140] QoS Provisioning In M2M Communications [92] Voice Capacity [246], [247] Resource Allocation…”

“…Underlay CRNs [143] Channel Errors Rayleigh Spectrum Sharing with Imperfect CSI [145] QoS with Interference Limitations Rayleigh Multiple Channel Spectrum Sharing [148] Interference Limitations Rayleigh Spectrum Sensing In CRNs [235] Channel Gain Rayleigh [236] Analysis of Outdated CSI Not Defined [128] General Fading α − µ CRNs with Various Fading Conditions [129] General Fading α − µ [115] Different QoS Applications Nakagami-m [234] Optimal Power Allocation Rayleigh Resource Allocation [137] Trade-off Between SUs and PUs performance Rayleigh [237] Interference Power Constraint Gamma Fading [153] Power Allocation with Imperfect CSI Rayleigh [102] Power Allocation with Imperfect CSI Rayleigh [110] Securing the CRNs Nakagami-m [172] Optimal Power Allocation Rayleigh [116] Optimal Power Allocation Nakagami-m [124] Optimal Power Allocation Nakagami-M CR-Based MAC [118] Rate and Power Estimation with MQAM Nakagami-m Modulation In CRNs [120] Power Estimation with MQAM Nakagami-m [203] SUs Throughput Rayleigh FDMA-Based CRNs [142] SUs arrival rate Rayleigh CR-Relay Networks [158] Interference and Delay Constraints Rayleigh [195] SUs Capacity Rayleigh Overlay CRNs [157] Power Level based on PUs Rayleigh Spectrum Sensing In CRNs [198] SUs Arrival Rate Rayleigh [155] Performance Limitations of SUs Rayleigh Interference Limitations In CRNs [238] SUs Capacity Analysis Asymmetric Fading [239] Channel Estimation Error Nakagami-m CRNs with MISO Systems [240] Two phase channel Access Method Not Defined Channel Access In CRNs [241] Hopping Based Channel Access Not Defined [225] Optimal Power Allocation Gamma Fading Resource Allocation [103] SUs Arrival Rate Nakagami-m…”

Resource Allocation with Successive Coding for OFDM-Based Cognitive System Subject to Statistical CSI

“…Thus, several research works have dealt with the resource allocation subject to partial channel knowledge for CR systems. More specifically, the impact of imperfect Channel State Information (CSI) was investigated in [8][9][10][11][12][13] with uncertainty, quantization, or estimation errors. In [8], the authors considered a cognitive underlay scenario assuming that the secondary receiver has only partial information of the link between its transmitter and the primary receiver.…”

“…This paper studied different capacity regions considering average or peak interference constraints at the primary receiver and introduced the concept of interference outage allowed by the primary receiver. The same problem was considered in [9] with average received power constraint at the primary receiver in a discrete-time block-fading channel with imperfect CSI. In [10], Suraweera et al investigated the impact of imperfect CSI of the SU-PU link on the SU mean capacity, considering the effect of CSI quantization with a finite number of quantization levels.…”